CN111882550A - Hail detection method, hail detection device, computer equipment and readable storage medium - Google Patents

Abstract

The present application relates to a hail detection method, device, computer equipment and readable storage medium. The method includes: acquiring a background image corresponding to a target area, the background image being generated based on at least one historical real image corresponding to the target area that does not include hail; acquiring at least one target real image corresponding to the target area, Comparing the target real scene image with the background image to obtain a comparison result, where the comparison result includes the pixel value change information of the target real scene image relative to the background image; and according to the comparison result, obtain the The hail detection result of the target area, the hail detection result is used to indicate that there is hail in the target area or there is no hail in the target area. The adoption of the method can reduce the cost of hail detection, is easy to implement, and improves the universality of hail detection.

Description

Hail detection method, device, computer equipment and readable storage medium

technical field

The present application relates to the technical field of meteorological detection, and in particular, to a hail detection method, device, computer equipment and readable storage medium.

Background technique

Hail is a weather phenomenon in which rising water vapour meets plummeting temperatures and is most common in summer or around the turn of spring and summer. Hail has strong destructive power. Hail damage often occurs in houses, vehicles, farmland, trees, and people or livestock. It is one of the serious natural disasters.

At present, the mainstream method to detect hail is to deploy dual-polarization Doppler weather radar, transmit horizontal and vertical polarization signals through the radar's transmitter, and process the data in parallel through the radar's dual-channel receiver and digital intermediate frequency. A specific algorithm (such as the NEX-TRAD hail detection algorithm in the United States) is used to detect hail.

However, the above method of detecting hail requires the deployment of dual-polarization Doppler weather radar, which is costly to deploy, and hail detection is limited by the implementation authority of a specific algorithm, resulting in poor universality of hail detection. Be applicable. Therefore, it is an urgent problem to provide a low-cost and easy-to-implement hail detection method.

SUMMARY OF THE INVENTION

Based on this, it is necessary to provide a low-cost and easy-to-implement hail detection method, device, computer device, and readable storage medium for the above technical problems.

In the first aspect, the embodiments of the present application provide a method for detecting hail, the method comprising:

Obtain a background image corresponding to the target area, the background image is generated based on at least one historical real image corresponding to the target area that does not include hail;

Acquire at least one target real-life image corresponding to the target area, and compare the target real-life image with the background image to obtain a comparison result, where the comparison result includes the pixels of the target real-life image relative to the background image value change information;

According to the comparison result, the hail detection result of the target area is obtained, and the hail detection result is used to indicate that there is hail in the target area or there is no hail in the target area.

In one of the embodiments, the at least one target real-life image is a plurality of target real-life images, and each of the target real-life images is consecutive in time sequence.

In one embodiment, the background image includes a reference background pixel area, and comparing the target real-life image with the background image to obtain a comparison result includes:

For each of the target real-life images, determining a target pixel area corresponding to the reference background pixel area from the target real-life image;

Differentiate the pixel value of each pixel in the target pixel area with the pixel value of the corresponding pixel in the reference background pixel area to obtain a difference result;

A difference result of each of the target real-life images is determined as the comparison result.

In one embodiment, obtaining the hail detection result of the target area according to the comparison result, including:

For each of the target real-life images, detect whether the difference result of each pixel in the target pixel area in the target real-life image is greater than a preset difference threshold;

A plurality of target pixel points whose difference result is greater than the preset difference threshold value are determined from each pixel point of the target pixel area, and a mask map corresponding to the target real scene image is generated according to the plurality of target pixel points , the mask map includes a plurality of mask regions formed by the plurality of target pixels;

Detecting whether the attribute information of the multiple mask areas satisfies a preset attribute condition, the preset attribute condition is related to the area of each of the mask areas and the number of the multiple mask areas;

If the attribute information of multiple mask areas of at least one target real-world image satisfies the preset attribute condition, it is determined that the hail detection result is that there is hail in the target area.

In one embodiment, after obtaining the hail detection result of the target area according to the comparison result, the method further includes:

If the hail detection result is that there is hail in the target area, obtain at least one updated real scene image corresponding to the target area, and perform accuracy verification on the hail detection result based on the at least one updated real scene image;

When the hail detection result passes the accuracy verification, output the hail detection result.

In one embodiment, after obtaining the hail detection result of the target area according to the comparison result, the method further includes:

If the hail detection result is that there is hail in the target area, obtain environmental data corresponding to the target area, and the environmental data includes at least one of temperature and air humidity corresponding to the target area;

Detecting whether the environmental data satisfies the environmental conditions produced by the hail;

If the environmental data satisfies the environmental condition for hail generation, output the hail detection result.

In one embodiment, after obtaining the hail detection result of the target area according to the comparison result, the method further includes:

If the hail detection result is that there is hail in the target area, measure the current distance information between the ranging component and the preset target in the target area by the ranging component;

Detect whether the difference between the current distance information and the reference distance information corresponding to the target area is greater than a preset distance threshold, and the reference distance information is that when there is no hail in the target area, through the measurement distance information between the distance measuring component and the preset target measured by the distance component;

If the difference between the current distance information and the reference distance information is greater than the preset distance threshold, output the hail detection result.

In one embodiment, after obtaining the hail detection result of the target area according to the comparison result, the method further includes:

If the hail detection result is that there is hail in the target area, then send hail prompt information to the user terminal, and the hail prompt information is used to prompt that there is hail in the target area;

If a video viewing request sent by the user terminal is received, the hail video data corresponding to the target area is acquired, and the hail video data is sent to the user terminal.

In a second aspect, an embodiment of the present application provides a hail detection device, the device comprising:

a first acquisition module, configured to acquire a background image corresponding to the target area, the background image is generated based on at least one historical real image corresponding to the target area that does not include hail;

A comparison module, configured to acquire at least one target real-life image corresponding to the target area, and compare the target real-life image with the background image to obtain a comparison result, where the comparison result includes the relative relationship between the target real-life image and the background image. Describe the pixel value change information of the background image;

The second obtaining module is configured to obtain the hail detection result of the target area according to the comparison result, where the hail detection result is used to indicate that there is hail in the target area or that there is no hail in the target area.

In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the method in the first aspect when the processor executes the computer program.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the steps of the method in the first aspect.

The beneficial effects brought by the technical solutions provided in the embodiments of the present application include at least:

By acquiring a background image corresponding to the target area, the background image is generated based on at least one historical real image corresponding to the target area that does not include hail, and acquiring at least one target real image corresponding to the target area, and comparing the target real image with the background image Carry out a comparison to obtain a comparison result, the comparison result includes the pixel value change information of the target real image relative to the background image, and then according to the comparison result, the hail detection result of the target area is obtained, and the hail detection result is used to indicate the presence of hail in the target area or the target area. There is no hail; thus, the target real-life image of the target area is compared with the background image, and after obtaining the comparison result including the pixel value change information of the target real-life image relative to the background image, it can be determined whether the target area exists according to the comparison result. Hail; avoids the need to deploy dual-polarization Doppler weather radar and combine specific algorithms (such as NEX-TRAD hail detection algorithm) to detect hail in traditional technology. Due to the high cost of radar deployment, and the hail detection algorithm needs to obtain the corresponding authorization, The resulting hail detection is not universally applicable, especially for some individual users. The embodiment of the present application only needs to acquire image data without deploying radar during hail detection, thereby reducing the cost of hail detection, and the hail detection process does not need to be combined with specific hail detection algorithms such as NEX-TRAD, so it is not necessary to acquire these specific algorithms It is easy to implement and improves the universality of hail detection.

Description of drawings

Fig. 1 is the schematic flow sheet of hail detection method in one embodiment;

FIG. 2 is a schematic diagram of part of the refinement steps of step S200 in another embodiment;

FIG. 3 is a schematic diagram of the refinement steps of step S300 in another embodiment;

Fig. 4 is the schematic flow sheet of the hail detection method in another embodiment;

5 is a schematic flowchart of a hail detection method in another embodiment;

Fig. 6 is the schematic flow sheet of the hail detection method in another embodiment;

Figure 7 is a schematic diagram of a hail detection system in one embodiment.

Fig. 8 is the structural block diagram of the hail detection device in one embodiment;

Figure 9 is a diagram of the internal structure of a computer device in one embodiment.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

The hail detection method, device, computer equipment, and readable storage medium provided by the embodiments of the present application are intended to solve the problem of the hail detection method in the traditional technology, due to the high cost of radar deployment and the need to obtain corresponding authorization for a specific hail detection algorithm. Technical problems with poor universality. The technical solutions of the present application will be specifically described in detail below with reference to the accompanying drawings. The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

It should be noted that, in the hail detection method provided by the embodiment of the present application, its execution body can be a hail detection device, and the hail detection device can be realized as part or all of computer equipment through software, hardware or a combination of software and hardware. Can be a server. In the following method embodiments, the execution subject is a computer device as an example for description. It can be understood that the hail detection method provided by the following method embodiments can also be applied to a terminal, and can also be applied to a system including a terminal and a server, and is implemented through interaction between the terminal and the server.

In one embodiment, as shown in Figure 1, a kind of hail detection method is provided, comprising the following steps:

Step S100, acquiring a background image corresponding to the target area.

In this embodiment of the present application, the target area may be an area where hail detection needs to be performed, for example, may be a specific road, a user living area, farmland, and the like. The computer device acquires a background image corresponding to the target area, and the background image may be generated by the computer device based on at least one historical real image corresponding to the target area that does not include hail. As an embodiment, after the computer device generates the background image, the background image can be stored in the database of the computer device corresponding to the target area. When the target area needs to be detected for hail, the computer device obtains the background image from the database. image. The background image is used as a reference background when there is no hail in the target area during the hail detection process.

As an implementation manner, the computer device may collect at least one historical real image corresponding to the target area that does not include hail by using the collection component at a historical moment. For example, in an environment with clear historical weather, the computer device controls the acquisition component to collect multiple historical real-life images of the target area, and the sampling moments corresponding to the multiple historical real-life images may be continuous. Since hail is mostly white, when the acquisition component is deployed, the acquisition picture can be fixed at a fixed building or other non-white background in the target area. The fixed building or non-white background can form a significant color difference with the hail. In this way, the computer equipment will be based on multiple When a background image generated by a historical real image is used as a reference background, it is beneficial for computer equipment to visually separate hail according to chromatic aberration.

The computer device generates a background image based on multiple historical reality images. In a possible implementation, the computer device can call the cv2.Canny function in the OpenCV vision library to extract contours from the multiple historical reality images, and then call the cv2.findContours function. Find connected areas (that is, the area enclosed by end-to-end line segments) from the extracted contours, and call the cv2.contourArea function to obtain the area of each connected area, then call the cv2.drawContours function to fill the small area of connected areas, and call cv2. The getStructuringElement function and the cv2.dilate function perform area expansion, so that the smaller connected domains are connected as a whole to form the background, so as to obtain the background image.

Since the multiple historical real images are continuous in time sequence, that is, the lighting and other environments are similar, the computer equipment analyzes the unchanged pixels of the multiple historical real images through the above process, thereby extracting a background image, which is the same size as the historical real image. . As an example, when the acquisition component is deployed, the acquisition image is fixed at the fixed building in the target area as an example, the background image includes the reference background pixel area corresponding to the fixed building, and the reference background pixel is excluded from the background image. The pixel values of other regions outside the region are all 0 (ie black).

As time goes by, the acquisition component may become loose or the environment may change, which will cause a large difference between the background image stored by the computer device and the current actual environment. In order to reduce this difference, the computer device in the embodiment of the present application Based on a preset time period, the above process of generating a background image based on multiple historical real-life images can be periodically performed on the target area, and the stored background image can be updated, thereby ensuring the accuracy of the background image and improving the accuracy of the hail detection method. .

In the embodiment of the present application, the acquisition component may be a high-sensitivity imager. Due to its high-sensitivity characteristics, the high-sensitivity imager can collect images similar to those in daytime imaging even in the night or in an environment with poor light, so that it can The realization of all-weather detection of hail expands the time range of hail detection, which is beneficial to improve the reliability of hail detection.

Step S200: Obtain at least one target real-life image corresponding to the target area, and compare the target real-life image with the background image to obtain a comparison result.

The computer device collects at least one target real-world image corresponding to the target area through the acquisition component. In a possible embodiment, the at least one target reality image may be a target reality image; in another possible embodiment, the at least one target reality image may also be a plurality of target reality images, the plurality of target reality images Each target real image in the target real image is continuous in time sequence. For example, the computer equipment can collect the target real image at the current sampling time and the target real image at two consecutive sampling times before the current sampling time, then three consecutive targets are obtained. Live image.

It should be noted that, compared with a single target real image, multiple target real images with continuous time series can more accurately represent the real scene of the target area, that is, the current actual environment. The computer equipment adopts multiple target real-world images with continuous time series for hail detection, which can avoid using only one target real-world image, and if there is interference in the one target real-world image, the problem of reducing the accuracy of hail detection is conducive to improving hail detection. accuracy. In the embodiments of the present application, the implementation of the embodiments of the present application is described by taking the at least one target real-life image as a plurality of target real-life images as an example. Of course, in other embodiments, the computer device may also obtain the corresponding images of the target area. A target real scene image, and the target real scene image is compared with the background image to obtain a comparison result including the pixel value change information of the target real scene image relative to the background image, and according to the comparison result, obtain the hail detection result of the target area , there is no specific restriction here.

Since the acquisition picture of the acquisition component is fixed, the picture field of view and size of the target real-life image and the historical real-life image are the same. The computer device compares each target real scene image with the background image, which may be to compare the pixel value of each pixel point of the target real scene image with the pixel value of each pixel point of the background image. For example, for a target real-life image, the computer device can make the difference between the pixel value of each pixel of the target real-life image and the pixel value of the pixel at the corresponding position in the background image, so as to obtain the pixel value of the target real-life image relative to the background image. change information. The computer device compares each target real scene image with the background image respectively to obtain a comparison result, where the comparison result includes pixel value change information of each target real scene image relative to the background image.

Step S300, obtaining the hail detection result of the target area according to the comparison result.

Among them, the hail detection result is used to represent the presence of hail in the target area or the absence of hail in the target area. The computer equipment determines whether there is hail in the target area according to the comparison result.

In a possible implementation manner, the computer device may mark the pixel points in the target real-world image with a large difference in pixel value from the background image, and determine the size and density of the area formed by the marked pixels according to the size and density of the area. Whether there is hail in the target area; for example, if there is an area formed by many marked pixels in each target real-life image, and the area of the formed area matches the size ratio of the hail, it can be determined that there is hail in the target area.

In another possible implementation, since hailstones are mostly white, if there are many areas formed by marked pixels in each target real-life image, and the area of the formed areas matches the size ratio of the hailstones, the computer equipment will also It can be detected whether the color represented by the actual pixel value of these marked pixels in the target real image is white or close to white, and if so, it is further determined that there is hail in the target area.

In the embodiment of the present application, as an implementation manner, the computer device may be a microcomputer such as a Raspberry Pi (Raspberry Pi), and the cost of the microcomputer is low, so that the cost of the hail detection method can be further reduced.

In this embodiment, a background image corresponding to the target area is acquired, the background image is generated based on at least one historical real image corresponding to the target area that does not include hail, at least one target real image corresponding to the target area is acquired, and the target real image is Compare with the background image to obtain the comparison result, the comparison result includes the pixel value change information of the target real scene image relative to the background image, and then according to the comparison result, the hail detection result of the target area is obtained, and the hail detection result is used to characterize the presence of hail in the target area. Or there is no hail in the target area; thus, the target real scene image in the target area is compared with the background image, and after obtaining the comparison result including the pixel value change information of the target real scene image relative to the background image, the target can be determined according to the comparison result. Whether there is hail in the area; avoids the need to deploy dual-polarization Doppler weather radar and combine specific algorithms (such as NEX-TRAD hail detection algorithm) to detect hail in traditional technology. authorization, resulting in poor universality of hail detection, especially for some individual users. The embodiment of the present application only needs to acquire image data without deploying radar during hail detection, thereby reducing the cost of hail detection, and the hail detection process does not need to be combined with specific hail detection algorithms such as NEX-TRAD, so it is not necessary to acquire these specific algorithms It is easy to implement and improves the universality of hail detection.

In one embodiment, on the basis of the above-mentioned embodiment shown in FIG. 1 and referring to FIG. 2 , this embodiment relates to how a computer device converts each target to a situation in which at least one target reality image is a plurality of target reality images. The process of comparing the real image with the background image and obtaining the comparison result. As shown in Figure 2, the process includes steps S201, S202 and S203:

Step S201 , for each target real scene image, determine a target pixel area corresponding to the reference background pixel area from the target real scene image.

In this embodiment of the present application, the background image includes a reference background pixel area. The reference background pixel area corresponds to the background in the target area. Taking the acquisition component as an example of a fixed building in the target area when the acquisition component is deployed, the reference background pixel area is the area corresponding to the fixed building in the background image. The pixel values of the reference background pixel area in the background image are real pixel values, and the pixel values of other areas in the background image except the reference background pixel area are all 0.

Since the acquisition screen of the acquisition component is fixed, the size of the target real scene image and the background image is the same, and the area in the target real scene image corresponding to the reference background pixel area of the background image is the target pixel area. For each target real-life image, the computer device determines the target pixel area from the target real-life image, which may be to determine the target pixel area in the target real image with the same location as the reference background pixel area.

In another possible implementation, for each target real image, the computer device can also detect whether the pixel value of each pixel in the background image is 0, and if it is 0, it is determined that the pixel at this position in the background image is not Refer to the background pixel area, therefore, it is determined that the pixel at this position in the target live image is not in the target pixel area; similarly, if it is not 0, it is determined that the pixel at this position in the target live image is the target pixel. Therefore, by sequentially detecting each pixel in the target real-life image, the target pixel area in the target real-life image can be determined.

In step S202, the pixel value of each pixel in the target pixel area is respectively different from the pixel value of the corresponding pixel in the reference background pixel area to obtain a difference result.

In the embodiment of the present application, the computer device compares the target real scene image with the background image, which may be the difference between the pixel value of each pixel point in the target pixel area and the pixel value of the corresponding position pixel point in the reference background pixel area to obtain the difference result.

It can be understood that the computer equipment only compares the target real scene image with the partial area in the background image (the target pixel area and the reference background pixel area), which can improve the comparison efficiency, thereby shortening the hail detection time, which is conducive to the realization of Real-time detection of hail, and can save computing resources of computer equipment.

Step S203, determining the difference result of each target real scene image as the comparison result.

The computer equipment determines the difference result of the real-life images of each target as the comparison result.

Based on the embodiment shown in FIG. 2, correspondingly, referring to FIG. 3, step S300 may include step S301, step S302, step S303 and step S304:

Step S301 , for each target real scene image, detect whether the difference result of each pixel point in the target pixel area in the target real scene image is greater than a preset difference threshold.

For each target real-life image, the computer device detects whether the difference result of each pixel point in the target pixel area in the target real-life image is greater than a preset difference threshold. It can be understood that, in the case where there is no hail in the target area, since the capture image of the capture component is fixed, the pixel values of the pixels at the corresponding positions in the target real image and the background image should be the same or similar.

Step S302: Determine a plurality of target pixels whose difference result is greater than a preset difference threshold from each pixel in the target pixel area, and generate a mask map corresponding to the target real image according to the plurality of target pixels.

If the difference result of pixel points in the target pixel area is greater than the preset difference threshold, it indicates that there is a change factor in the target pixel area, such as the imaging of the hail falling process, which belongs to the change factor. The computer device can determine the pixel points whose difference result is greater than the preset difference threshold value as the target pixel point, and mark each target pixel point in the target real scene image, and classify the other pixels except the target pixel point in the target real scene image. If the pixel value of the point is set to 0, the mask map corresponding to the target real scene image is obtained. The mask map includes multiple mask regions formed by multiple target pixels.

Step S303: Detect whether the attribute information of the multiple mask regions satisfies a preset attribute condition.

In this embodiment of the present application, the preset attribute condition is related to the area of each mask area and the number of multiple mask areas. The computer equipment can set preset attribute conditions according to the characteristics of the hail falling process. For example, the preset attribute conditions can be set as the area of the mask area is within the area of the hail imaging area, and the number of mask areas is not less than the amount of the hail falling. minimum quantity, etc.

The computer equipment detects whether the attribute information of the multiple mask areas in the mask map corresponding to each target real scene image satisfies the preset attribute conditions, for example, it can be detected whether the area of each mask area is within the area of the hail imaging area, Detects whether the number of mask areas included in the mask map is greater than the minimum number of hail falls. As an implementation manner, for the mask map, the computer device can call the cv2.findContours function in the OpenCV vision library to find the connected area, that is, the mask area, and then obtain the area of each mask area by calling the cv2.contourArea function.

Step S304, if the attribute information of multiple masked areas of at least one target real-life image satisfies the preset attribute condition, it is determined that the hailstone detection result is that there is hailstone in the target area.

If the attribute information of multiple mask areas in at least one target real-life image in the multiple target real-life images satisfies the preset attribute condition, the computer device determines that the hail detection result in the target area is that there is hail in the target area. That is, if there are many mask areas in the mask map corresponding to at least one target real-world image, and the area of the mask area is within the area of the hail imaging area, the hail detection result is determined to be hail in the target area. If the attribute information of the multiple mask areas of the consecutive multiple target real-life images all meet the preset attribute conditions, the hail detection result is also determined to be that there is hail in the target area, and in this case, the possibility of hail in the target area is higher. big.

In a possible implementation manner, after determining that there is hail in the target area, the computer device may also determine the hail intensity according to the area of each mask area and the number of multiple mask areas in each target real-life image. As an embodiment, the computer device can store the area interval of the mask area, the mapping relationship between the number interval of the mask area and the hail intensity, and the computer device can obtain the average value of each mask area in the mask map corresponding to the target real scene image. area and the number of masked areas, and then according to the average area and the number of masked areas, the corresponding area of masked area and the number of masked areas are searched in the mapping relationship, so that the corresponding hail intensity can be determined.

In this embodiment, the difference between the pixel value of each pixel in the target pixel area and the pixel value of the corresponding pixel in the reference background pixel area can improve the comparison efficiency, thereby shortening the hail detection time, which is conducive to the realization of real-time hail detection , and can save computing resources of computer equipment. In this embodiment, after it is determined that there is hail in the target area, the hail intensity of the target area is further obtained, which can provide the user with more refined hail detection data, thereby more effectively helping the user to make an anti-hail response in a timely manner, which is beneficial to reducing the risk of the user. loss and protect user safety.

On the basis of the above embodiment shown in FIG. 1 , referring to FIG. 4 , this embodiment is a process in which a computer device performs accuracy verification on a hail detection result in one embodiment. As shown in Figure 4, the hail detection method of the present embodiment further includes step S401 and step S402:

Step S401, if the hail detection result is that there is hail in the target area, obtain at least one updated real-life image corresponding to the target area, and verify the accuracy of the hail detection result based on the at least one updated real-world image.

In the embodiment of the present application, after the computer device determines that the hail detection result in the target area is that there is hail in the target area, the computer device acquires at least one updated real-world image corresponding to the target area, and based on the at least one updated real-life image, the hail detection result is accurate. verify.

In a possible implementation manner, the at least one updated real-life image may be one updated real-life image; in another possible implementation, the at least one updated real-life image may be a plurality of updated real-life images, each of which is updated It is continuous in time sequence, and the sampling interval between each updated live image is smaller than the sampling interval between each target live image.

As an embodiment, taking at least one updated real image as a plurality of updated real images as an example, after the computer device determines that the hail detection result in the target area is that there is hail in the target area, the sampling interval can be reduced, and the acquisition component can be controlled to re-evaluate Continuous image sampling is performed on the target area to obtain multiple updated real-world images. The computer device can compare each updated real-life image with the target image in the manner of the embodiments shown in FIG. 2 and FIG. 3 , and detect whether there is hail in the target area according to the comparison result.

It should be noted that the implementation of the computer equipment detecting whether there is hail in the target area according to a plurality of updated real-life images and background images is the same as or similar to the implementation of the computer equipment detecting whether there is hail in the target area according to a plurality of target real-life images and background images. , for details, reference may be made to the foregoing embodiments, which will not be repeated here.

Step S402, in the case that the hail detection result passes the accuracy verification, output the hail detection result.

If the computer device determines that there is hail in the target area according to at least one updated real-world image, it is determined that the hail detection result passes the accuracy verification, and in the case that the hail detection result passes the accuracy verification, the hail detection result is output, for example, it can be sent to the user terminal. information to remind the target area that hail has occurred, to remind users to make anti-hail responses in time to reduce user losses and ensure user safety.

On the basis of the above embodiment shown in FIG. 1 , referring to FIG. 5 , this embodiment is a process in which a computer device performs accuracy verification on a hail detection result in another embodiment. As shown in FIG. 5, the hail detection method of the present embodiment further includes step S501, step S502 and step S503:

Step S501, if the hail detection result is that there is hail in the target area, obtain environmental data corresponding to the target area.

In the embodiment of the present application, after the computer device determines that the hail detection result in the target area is that there is hail in the target area, the computer device can obtain environmental data corresponding to the target area through sensors deployed in the target area, and the environmental data includes the corresponding environmental data in the target area. At least one of temperature and air humidity, the sensor may be a temperature and humidity sensor.

Step S502, detecting whether the environmental data meets the environmental conditions for hail generation.

The computer device detects whether the environmental data meets the environmental conditions for hail generation, and the environmental conditions can be associated with meteorological factors generated by hail, for example, the necessary humidity for hail generation can be used as a humidity threshold and the necessary temperature for hail generation can be used as a temperature threshold. The computer device can then detect whether the temperature included in the environmental data is lower than the temperature threshold and whether the humidity included in the environmental data is higher than the humidity threshold.

Step S503, if the environmental data meets the environmental conditions for hail generation, output the hail detection result.

If the environmental data meets the environmental conditions for hail generation, the computer equipment determines that the current environment of the target area is likely to form hail, further determines that the hail detection result is accurate, and then outputs the hail detection result, which can ensure the reliability of the hail detection result.

On the basis of the above embodiment shown in FIG. 1 , referring to FIG. 6 , this embodiment is a process in which a computer device performs accuracy verification on a hail detection result in another embodiment. As shown in FIG. 6, the hail detection method of the present embodiment further includes step S601, step S602 and step S603:

Step S601, if the hail detection result is that there is hail in the target area, measure the current distance information between the ranging component and a preset target in the target area by using the ranging component.

If the computer device detects that the hail detection result in the target area is that there is hail in the target area, in order to improve the reliability of the hail detection result, the computer device obtains the current distance between the ranging component and the preset target in the target area through the ranging component. information.

In this embodiment of the present application, the ranging component may be a laser ranging sensor. The laser ranging sensor is directed toward a preset target in the target area, and a laser beam is emitted to obtain the laser detection distance, that is, current distance information. It is understandable that if there is hail in the target area, the laser beam emitted by the laser ranging sensor may be blocked by the hail before reaching the preset target, which will shorten the round-trip transmission path of the laser, thereby shortening the distance. The preset target can be any target in the target area.

Step S602, detecting whether the difference between the current distance information and the reference distance information corresponding to the target area is greater than a preset distance threshold.

The computer equipment detects whether the difference between the current distance information and the reference distance information corresponding to the target area is greater than a preset distance threshold, wherein the reference distance information is the distance measured by the distance measuring component when there is no hail in the target area. The distance information between the component and the preset target, that is, the actual distance between the ranging component and the preset target. The preset distance threshold can be set by itself during implementation, for example, it can be set based on human experience.

Step S603, if the difference between the current distance information and the reference distance information is greater than a preset distance threshold, output a hail detection result.

If the computer device detects that the difference between the current distance information and the reference distance information corresponding to the target area is greater than the preset distance threshold, it indicates that the distance change is too large, then further determines that there is hail in the target area, and then outputs the hail that there is hail in the target area. Therefore, the reliability of the hail detection results can be ensured.

In one embodiment, on the basis of the above-mentioned embodiment, the hail detection method of the present embodiment may also include step A1 and step A2:

Step A1, if the hail detection result is that there is hail in the target area, send hail prompt information to the user terminal, and the hail prompt information is used to prompt that there is hail in the target area.

Step A2, if a video viewing request sent by the user terminal is received, obtain hail video data corresponding to the target area, and send the hail video data to the user terminal.

In a possible implementation, see FIG. 7 , which is a schematic diagram of a hail detection system in an embodiment. Taking the computer device as Raspberry Pi as an example, the Raspberry Pi communicates with the user terminal (Phone) through the communication module (GSM/HLS), and the Raspberry Pi controls the high-sensitivity imager (Camera) to collect the historical real scene of the target area Images, target real images and updated real images, etc., through sensors, such as temperature and humidity sensors to collect environmental data of the target area, laser ranging sensors to collect the laser detection distance of the target area, etc.

If the Raspberry Pi detects that there is hail in the target area, it will send a hail reminder message to the user terminal. The hail reminder message can carry a confirmation option, such as "Do you want to watch the video?", if the user clicks "Yes", the user The terminal sends a video viewing request to the Raspberry Pi. After receiving the video viewing request sent by the user, the Raspberry Pi controls the high-sensitivity imager to collect hail video data corresponding to the target area, and sends the hail video data to the user terminal. Therefore, it is beneficial for the user to understand the hail information in real time and more intuitively, such as the size and intensity of the hail, so as to avoid or reduce the adverse impact of the hail on the safety of the user's life and property, as well as the life and travel.

It should be understood that although the steps in the flowcharts of FIGS. 1-6 are shown in sequence according to the arrows, these steps are not necessarily executed in the sequence shown by the arrows. Unless explicitly stated herein, the execution of these steps is not strictly limited to the order, and these steps may be performed in other orders. Moreover, at least a part of the steps in FIGS. 1-6 may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but may be executed at different times. The execution of these steps or stages The order is also not necessarily sequential, but may be performed alternately or alternately with other steps or at least a portion of the steps or phases within the other steps.

In one embodiment, as shown in Figure 8, a hail detection device is provided, comprising:

The first acquisition module 10 is used to acquire a background image corresponding to the target area, and the background image is generated based on at least one historical real image corresponding to the target area that does not include hail;

The comparison module 20 is configured to obtain at least one target real-life image corresponding to the target area, and compare the target real-life image with the background image to obtain a comparison result, where the comparison result includes the relative relationship between the target real-life image and the background image. pixel value change information of the background image;

The second obtaining module 30 is configured to obtain the hail detection result of the target area according to the comparison result, where the hail detection result is used to indicate that there is hail in the target area or that there is no hail in the target area.

Optionally, the at least one target real-life image is a plurality of target real-life images, and each of the target real-life images is consecutive in time sequence.

Optionally, the background image includes a reference background pixel area, and the comparison module 20 includes:

a first determining unit, configured to, for each of the target real-life images, determine a target pixel area corresponding to the reference background pixel area from the target real-life image;

an arithmetic unit, used to make a difference between the pixel value of each pixel in the target pixel area and the pixel value of the corresponding pixel in the reference background pixel area, to obtain a difference result;

The second determination unit is configured to determine the difference result of each of the target real-life images as the comparison result.

Optionally, the second obtaining module 30 includes:

a first detection unit, configured to detect, for each of the target real-life images, whether the difference result of each pixel in the target pixel area in the target real-life image is greater than a preset difference threshold;

A mask map generating unit is used to determine a plurality of target pixels whose difference result is greater than the preset difference threshold from each pixel of the target pixel area, and generate the said target pixel according to the plurality of target pixels. a mask map corresponding to the target real scene image, the mask map including multiple mask regions formed by the multiple target pixels;

a second detection unit, configured to detect whether the attribute information of the multiple mask areas satisfies a preset attribute condition, the preset attribute condition is related to the area of each of the mask areas and the number of the multiple mask areas related;

A third determining unit, configured to determine that the hail detection result is that there is hail in the target area if the attribute information of multiple mask areas in at least one target real-life image meets the preset attribute condition.

Optionally, the device further includes:

A verification module, configured to obtain at least one updated real-world image corresponding to the target area if the hail detection result is that there is hail in the target area, and accurately perform the hail detection result based on the at least one updated real-world image sexual verification;

The first output module is configured to output the hail detection result when the hail detection result passes the accuracy verification.

Optionally, the device further includes:

A third acquisition module, configured to acquire environmental data corresponding to the target area if the hail detection result is that there is hail in the target area, and the environmental data includes at least one of the temperature and air humidity corresponding to the target area One;

a first detection module for detecting whether the environmental data meets the environmental conditions generated by hail;

The second output module is configured to output the hail detection result if the environmental data satisfies the environmental conditions generated by hail.

Optionally, the device further includes:

The fourth acquisition module is used for, if the hail detection result is that there is hail in the target area, then measure the current distance information between the ranging component and the preset target in the target area by the ranging component;

The second detection module is configured to detect whether the difference between the current distance information and the reference distance information corresponding to the target area is greater than a preset distance threshold, and the reference distance information is that there is no hail in the target area. In this case, the distance information between the ranging component and the preset target measured by the ranging component;

A third output module, configured to output the hail detection result if the difference between the current distance information and the reference distance information is greater than the preset distance threshold.

Optionally, the device further includes:

A prompting module, configured to send hail prompt information to the user terminal if the hail detection result is that there is hail in the target area, and the hail prompt information is used to prompt that there is hail in the target area;

A sending module, configured to acquire hail video data corresponding to the target area if a video viewing request sent by the user terminal is received, and send the hail video data to the user terminal.

For the specific limitation of the hail detection device, please refer to the limitation of the hail detection method above, which will not be repeated here. Each module in the above-mentioned hail detection device can be implemented in whole or in part by software, hardware and combinations thereof. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

In one embodiment, a computer device is provided, and the computer device may be a server, and its internal structure diagram may be as shown in FIG. 9 . The computer device includes a processor, memory, and a network interface connected by a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium, an internal memory. The nonvolatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the execution of the operating system and computer programs in the non-volatile storage medium. The database of the computer device is used to store the data of the hail detection method. The network interface of the computer device is used to communicate with an external terminal through a network connection. The computer program, when executed by the processor, implements a hail detection method.

Those skilled in the art can understand that the structure shown in FIG. 9 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer equipment to which the solution of the present application is applied. Include more or fewer components than shown in the figures, or combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, including a memory and a processor, a computer program is stored in the memory, and the processor implements the following steps when executing the computer program:

Obtain a background image corresponding to the target area, the background image is generated based on at least one historical real image corresponding to the target area that does not include hail;

Acquire at least one target real-life image corresponding to the target area, and compare the target real-life image with the background image to obtain a comparison result, where the comparison result includes the pixels of the target real-life image relative to the background image value change information;

According to the comparison result, the hail detection result of the target area is obtained, and the hail detection result is used to indicate that there is hail in the target area or there is no hail in the target area.

In one embodiment, the at least one target real-life image is a plurality of target real-life images, and each of the target real-life images is consecutive in time sequence.

In one embodiment, the background image includes a reference background pixel area, and the processor further implements the following steps when executing the computer program:

For each of the target real-life images, determining a target pixel area corresponding to the reference background pixel area from the target real-life image;

Differentiate the pixel value of each pixel in the target pixel area with the pixel value of the corresponding pixel in the reference background pixel area to obtain a difference result;

A difference result of each of the target real-life images is determined as the comparison result.

In one embodiment, the processor further implements the following steps when executing the computer program:

For each of the target real-life images, detect whether the difference result of each pixel in the target pixel area in the target real-life image is greater than a preset difference threshold;

A plurality of target pixel points whose difference result is greater than the preset difference threshold value are determined from each pixel point of the target pixel area, and a mask map corresponding to the target real scene image is generated according to the plurality of target pixel points , the mask map includes a plurality of mask regions formed by the plurality of target pixels;

Detecting whether the attribute information of the multiple mask areas satisfies a preset attribute condition, the preset attribute condition is related to the area of each of the mask areas and the number of the multiple mask areas;

If the attribute information of multiple mask areas of at least one target real-world image satisfies the preset attribute condition, it is determined that the hail detection result is that there is hail in the target area.

In one embodiment, the processor further implements the following steps when executing the computer program:

If the hail detection result is that there is hail in the target area, obtain at least one updated real scene image corresponding to the target area, and perform accuracy verification on the hail detection result based on the at least one updated real scene image;

When the hail detection result passes the accuracy verification, output the hail detection result.

In one embodiment, the processor further implements the following steps when executing the computer program:

If the hail detection result is that there is hail in the target area, obtain environmental data corresponding to the target area, and the environmental data includes at least one of temperature and air humidity corresponding to the target area;

Detecting whether the environmental data satisfies the environmental conditions produced by the hail;

If the environmental data satisfies the environmental condition for hail generation, output the hail detection result.

In one embodiment, the processor further implements the following steps when executing the computer program:

If the hail detection result is that there is hail in the target area, measure the current distance information between the ranging component and the preset target in the target area by the ranging component;

Detect whether the difference between the current distance information and the reference distance information corresponding to the target area is greater than a preset distance threshold, and the reference distance information is that when there is no hail in the target area, through the measurement distance information between the distance measuring component and the preset target measured by the distance component;

If the difference between the current distance information and the reference distance information is greater than the preset distance threshold, output the hail detection result.

In one embodiment, the processor further implements the following steps when executing the computer program:

If the hail detection result is that there is hail in the target area, then send hail prompt information to the user terminal, and the hail prompt information is used to prompt that there is hail in the target area;

If a video viewing request sent by the user terminal is received, the hail video data corresponding to the target area is acquired, and the hail video data is sent to the user terminal.

In one embodiment, a computer-readable storage medium is provided on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

Obtain a background image corresponding to the target area, the background image is generated based on at least one historical real image corresponding to the target area that does not include hail;

Acquire at least one target real-life image corresponding to the target area, and compare the target real-life image with the background image to obtain a comparison result, where the comparison result includes the pixels of the target real-life image relative to the background image value change information;

According to the comparison result, the hail detection result of the target area is obtained, and the hail detection result is used to indicate that there is hail in the target area or there is no hail in the target area.

In one embodiment, the at least one target real-life image is a plurality of target real-life images, and each of the target real-life images is consecutive in time sequence.

In one embodiment, the background image includes a reference background pixel area, and the computer program further implements the following steps when executed:

For each of the target real-life images, determining a target pixel area corresponding to the reference background pixel area from the target real-life image;

Differentiate the pixel value of each pixel in the target pixel area with the pixel value of the corresponding pixel in the reference background pixel area to obtain a difference result;

A difference result of each of the target real-life images is determined as the comparison result.

In one embodiment, the computer program, when executed, also implements the following steps:

For each of the target real-life images, detect whether the difference result of each pixel in the target pixel area in the target real-life image is greater than a preset difference threshold;

A plurality of target pixel points whose difference result is greater than the preset difference threshold value are determined from each pixel point of the target pixel area, and a mask map corresponding to the target real scene image is generated according to the plurality of target pixel points , the mask map includes a plurality of mask regions formed by the plurality of target pixels;

Detecting whether the attribute information of the multiple mask areas satisfies a preset attribute condition, the preset attribute condition is related to the area of each of the mask areas and the number of the multiple mask areas;

If the attribute information of multiple mask areas of at least one target real-world image satisfies the preset attribute condition, it is determined that the hail detection result is that there is hail in the target area.

In one embodiment, the computer program, when executed, also implements the following steps:

If the hail detection result is that there is hail in the target area, obtain at least one updated real scene image corresponding to the target area, and perform accuracy verification on the hail detection result based on the at least one updated real scene image;

When the hail detection result passes the accuracy verification, output the hail detection result.

In one embodiment, the computer program, when executed, also implements the following steps:

If the hail detection result is that there is hail in the target area, obtain environmental data corresponding to the target area, and the environmental data includes at least one of temperature and air humidity corresponding to the target area;

Detecting whether the environmental data satisfies the environmental conditions produced by the hail;

If the environmental data satisfies the environmental condition for hail generation, output the hail detection result.

In one embodiment, the computer program, when executed, also implements the following steps:

If the hail detection result is that there is hail in the target area, measure the current distance information between the ranging component and the preset target in the target area by the ranging component;

Detect whether the difference between the current distance information and the reference distance information corresponding to the target area is greater than a preset distance threshold, and the reference distance information is that when there is no hail in the target area, through the measurement distance information between the distance measuring component and the preset target measured by the distance component;

If the difference between the current distance information and the reference distance information is greater than the preset distance threshold, output the hail detection result.

In one embodiment, the computer program, when executed, also implements the following steps:

If the hail detection result is that there is hail in the target area, then send hail prompt information to the user terminal, and the hail prompt information is used to prompt that there is hail in the target area;

If a video viewing request sent by the user terminal is received, the hail video data corresponding to the target area is acquired, and the hail video data is sent to the user terminal.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage In the medium, when the computer program is executed, it may include the processes of the above-mentioned method embodiments. Wherein, any reference to memory, storage, database or other media used in the various embodiments provided in this application may include at least one of non-volatile and volatile memory. The non-volatile memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, and the like. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, the RAM may be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM).

The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, all It is considered to be the range described in this specification.

The above-mentioned embodiments only represent several embodiments of the present application, and the descriptions thereof are specific and detailed, but should not be construed as a limitation on the scope of the invention patent. It should be pointed out that for those skilled in the art, without departing from the concept of the present application, several modifications and improvements can be made, which all belong to the protection scope of the present application. Therefore, the scope of protection of the patent of the present application shall be subject to the appended claims.

Claims (10)

1. A hail detection method, characterized in that the method comprises:

acquiring a background image corresponding to a target area, wherein the background image is generated based on at least one historical live-action image which does not include hail and corresponds to the target area;

acquiring at least one target live-action image corresponding to the target area, and comparing the target live-action image with the background image to obtain a comparison result, wherein the comparison result comprises pixel value change information of the target live-action image relative to the background image;

and acquiring a hail detection result of the target area according to the comparison result, wherein the hail detection result is used for representing that hail exists in the target area or the hail does not exist in the target area.

2. The method of claim 1, wherein the at least one target real-world image is a plurality of target real-world images, each of the target real-world images being chronologically continuous.

3. The method of claim 2, wherein the background image comprises a reference background pixel region, and the comparing the target real-scene image with the background image to obtain a comparison result comprises:

for each target real-scene image, determining a target pixel region corresponding to the reference background pixel region from the target real-scene image;

respectively subtracting the pixel value of each pixel point in the target pixel region from the pixel value of the corresponding pixel point in the reference background pixel region to obtain a subtraction result;

and determining the difference result of each target real-scene image as the comparison result.

4. The method according to claim 3, wherein said obtaining a hail detection result of said target area based on said comparison result comprises:

detecting whether the difference result of each pixel point of a target pixel area in each target live-action image is larger than a preset difference threshold value or not according to each target live-action image;

determining a plurality of target pixel points with the difference result larger than the preset difference threshold value from all pixel points of the target pixel area, and generating a mask image corresponding to the target real-scene image according to the plurality of target pixel points, wherein the mask image comprises a plurality of mask areas formed by the plurality of target pixel points;

detecting whether attribute information of the mask regions meets a preset attribute condition, wherein the preset attribute condition is related to the area of each mask region and the number of the mask regions;

and if the attribute information of a plurality of mask regions of at least one target live-action image meets the preset attribute condition, determining that the hail detection result is that hail exists in the target region.

5. The method according to claim 1, wherein after obtaining a hail detection result of the target area according to the comparison result, further comprising:

if the hail detection result indicates that hail exists in the target area, acquiring at least one updated live-action image corresponding to the target area, and performing accuracy verification on the hail detection result based on the at least one updated live-action image;

and under the condition that the hail detection result passes the accuracy verification, outputting the hail detection result.

6. The method according to claim 1, wherein after obtaining a hail detection result of the target area according to the comparison result, further comprising:

if the hail detection result indicates that hail exists in the target area, acquiring environment data corresponding to the target area, wherein the environment data comprises at least one of temperature and air humidity corresponding to the target area;

detecting whether the environmental data meets an environmental condition for hail generation;

and if the environmental data meets the environmental condition generated by hail, outputting the hail detection result.

7. The method according to claim 1, wherein after obtaining a hail detection result of the target area according to the comparison result, further comprising:

if the hail detection result indicates that hail exists in the target area, measuring current distance information between the distance measurement assembly and a preset target object in the target area through the distance measurement assembly;

detecting whether a difference value between the current distance information and reference distance information corresponding to the target area is greater than a preset distance threshold, wherein the reference distance information is the distance information between the ranging assembly and a preset target object measured by the ranging assembly under the condition that hail does not exist in the target area;

and if the difference value of the current distance information and the reference distance information is larger than the preset distance threshold, outputting the hail detection result.

8. The method according to claim 1, wherein after obtaining a hail detection result of the target area according to the comparison result, further comprising:

if the hail detection result indicates that hail exists in the target area, hail prompt information is sent to a user terminal, and the hail prompt information is used for prompting that hail exists in the target area;

and if a video viewing request sent by the user terminal is received, acquiring hail video data corresponding to the target area, and sending the hail video data to the user terminal.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 8.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 8.

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