CN106841673A - Device and method for measuring average flow velocity on river surface - Google Patents

Abstract

The present invention provides a method and system for measuring the average flow velocity of a river surface. The method includes: based on the river surface images at the current moment and the previous moment, obtaining the salient point or region of motion in the river surface image at the current moment ; Obtain the average displacement within a certain period of time based on the salient point of motion or the significant region of motion at each moment within a certain period of time; the average flow rate within. The invention does not need to throw buoys on the water surface, and can measure the flow velocity continuously.

Description

Device and method for measuring average flow velocity on river surface

technical field

The invention relates to the field of image processing, and more particularly, to a device and method for measuring the average flow velocity of a river surface.

Background technique

There are many rivers in our country, and the comprehensive utilization of rivers has always occupied an important position in the national economic and social development of our country. Hydrological monitoring information plays an important role in the prevention and control of floods, floods and droughts, and the regulation of water resources. The flow rate measurement is one of the important tasks of hydrological monitoring, but the current flow rate measurement methods have certain limitations. The commonly used river flow velocity measurement methods are mainly divided into three categories.

The first type is the traditional flow meter measurement method. Its main principle is to drive the propeller to rotate through the water flow, record the propeller speed, and calculate the flow velocity through a certain mapping relationship. However, when the water quality changes suddenly and the sediment concentration increases, the error will increase become larger, and the floating objects in the water will affect the result and even damage the propeller.

The second type is to measure the flow velocity through the acoustic Doppler effect, which is mainly used for measuring ships, but there are also problems of relatively large investment in equipment and human beings, and relatively high costs.

The third category is the water velocity measurement method based on the combination of video processing and buoy method. The movement trajectory of the frequency mid-frequency buoy is combined with camera calibration to calculate the water velocity.

Two examples of the third category of methods are: (1) Invention patent "Image processing system and its synchronous real-time measurement method for large-scale surface flow velocity" (application number CN1289037A, 2000), (2) "Video-based river water processing Flow Velocity Monitoring System Design" (Han Yuwan, Taiyuan University of Technology Master Thesis, 2010). Both examples use the combination of buoy method and image processing. When using it, you need to put in a buoy, and then track the movement of the buoy or tracer particles in the video. In these two examples, the tracking principle adopted is based on the obvious difference in color between the buoy and the water surface, with the water surface as the background and the buoy as the tracking target. However, this method needs to throw a buoy into the field of view of the camera. When the buoy floats out of the field of view of the camera, the flow velocity cannot be detected, and the uninterrupted real-time measurement of the water flow velocity cannot be realized. At the same time, the throwing and recovery of the buoy is also very troublesome.

Contents of the invention

The present invention provides a device and method for measuring the average flow velocity of a river surface which overcomes the above-mentioned problems or at least partly solves the above-mentioned problems.

According to one aspect of the present invention, there is provided a method of measuring the average flow velocity of a river surface, comprising:

S1. Based on the river surface image at the current moment and the previous moment, obtain the salient point or region of motion in the river surface image at the current moment;

S2. Obtain an average displacement within a certain period of time based on the significant points of movement or the significant regions of movement at each moment within a certain period of time; and

S3. Obtain an average flow velocity within a certain period of time based on the scale calibration coefficient, the average displacement within the certain period of time, and the time between frames.

According to another aspect of the present invention, there is also provided a system for measuring the average velocity of a river surface, comprising:

A motion salience detection device, used to obtain a motion salience point or a motion salience area of the river surface image at the current moment based on the river surface image at the current moment and the previous moment;

An average displacement detection device, connected to the motion salience detection device, based on the motion salience point or motion salience area at each moment within a certain period of time, to obtain the average displacement within a certain period of time; and

The average flow velocity detection device is connected with the average displacement detection device, and the average flow velocity detection device is used to obtain the average flow velocity within a certain period of time based on the scale calibration coefficient, the average displacement at each moment within a certain period of time, and the time between frames.

This application obtains river video through a camera perpendicular to the water surface, analyzes the feature map with significant motion, extracts the significant motion area or point, and tracks the displacement corresponding to each significant motion area or point , the actual flow velocity on the river surface is calculated by combining the image coordinate system and the position mapping relationship with the real space coordinate system and the time between frames. This application does not need to throw buoys on the water surface, but can use the fluctuating texture characteristics or natural floating objects generated during the flow of river water to measure the average flow velocity of the river surface, and the flow velocity can be measured continuously.

Description of drawings

Fig. 1 is a kind of flow chart of the method for measuring the average flow velocity of river surface according to the embodiment of the present invention;

Fig. 2 is a histogram of a method for measuring the average velocity of a river surface according to an embodiment of the present invention;

Fig. 3 is a structural block diagram of a system for measuring the average velocity of a river surface according to an embodiment of the present invention.

detailed description

The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

In order to overcome the problem in the prior art that it is necessary to throw buoys on the water surface, the flow velocity cannot be detected when the buoy floats out of the field of view of the camera, and the problem of troublesome throwing and recovery, the present invention provides a method that utilizes the flow of river water itself It is a method of measuring the average velocity of the river surface by fluctuating texture features or natural floating objects, and continuously measuring the velocity of the velocity.

Fig. 1 shows a flow chart of a method for measuring the average velocity of a river surface according to an embodiment of the present invention, including:

S1. Based on the river surface image at the current moment and the previous moment, obtain the salient point or region of motion in the river surface image at the current moment;

S2. Obtain an average displacement within a certain period of time based on the significant points of movement or the significant regions of movement at each moment within a certain period of time; and

S3. Obtain an average flow velocity within a certain period of time based on the scale calibration coefficient, the average displacement within the certain period of time, and the time between frames.

The present invention obtains river video (sequence images) through a camera perpendicular to the water surface, analyzes the feature map with significant motion, extracts the motion salient feature points, tracks the pixel displacement corresponding to each motion salient feature point, and simultaneously The image coordinate system and the position mapping relationship with the real space coordinate system and the time between frames are used to calculate the actual flow velocity of the river surface.

In one embodiment, the present invention provides a method for obtaining an average displacement based on a motion salient area, wherein the step S1 includes:

S1.1. Based on the frame difference between the river surface image P t at time _t and the river surface image P t-1 at time _t-1 , obtain the motion saliency feature map x t at time _t . Similarly, based on the river surface image P _{t+1 at time t+1} and the river surface image P _t at time t, the motion saliency feature map x _t+ 1 at time t+1 is obtained.

Frame difference, also known as inter-frame difference, is a method of obtaining the outline of a moving target by performing a differential operation on two adjacent frames in a video image sequence, which can be well suited for multiple moving targets and camera movement Case. When abnormal objects move in the monitoring scene, there will be obvious differences between frames. Subtract the two frames to get the absolute value of the brightness difference between the two frames, and judge whether it is greater than the threshold to analyze the motion of the video or image sequence. feature to determine the presence or absence of object motion in an image sequence.

S1.2. Based on the motion saliency feature map at the current moment, obtain the motion saliency region of the river surface image at the current moment.

In one embodiment, the step S1.2 includes:

S1.2.1. Binarize the motion saliency feature map at time t to obtain a binary map. The binarization of the image is to set the gray value of the pixels on the image to 0 or 255, that is, to present the entire image with an obvious visual effect of only black and white. The most commonly used method is to set a threshold T, and use T to divide the data of the image into two parts: the pixel group larger than T and the pixel group smaller than T.

S1.2.2. Select N _t,1 connected domains on the binary image, and any one of the connected domains is a rectangle with a length or width of 20-100 pixels. The most important method of binary image analysis is connected area marking, which is the basis of all binary image analysis. It allows each individual connected area to form a marked by marking the white pixels (targets) in the binary image. A block is a connected domain.

S1.2.3, using the connected domain as a mask, the mask is the outside of the marquee (the inside of the marquee is the constituency), find the position corresponding to the connected domain in the motion saliency feature map at time t, as the Motion salient regions, the set of these motion salient regions is denoted as {ft _,i }(i=1,2,...,N _t,1 |t=1,2,...).

In one embodiment, the binarization threshold is 0.9 times the maximum gray value of the motion saliency feature map.

In one embodiment, the step S2 includes:

S2.1. Search for a matching region that matches each motion salient region at time t-1 in the salient feature map at time t;

S2.2. Calculate the relative displacement of the matching region in the motion saliency feature map from time t-1 to time t; and

S2.3. Obtain a histogram of relative displacement based on the relative displacement of the corresponding matching area at each moment within a certain period of time, and use the average value of the peak value in the histogram and a certain range of values near the peak value as the certain Average displacement over time.

For a template f _t,i , if the matching area can be found in the motion saliency feature map x _t+1 , calculate the relative displacement between the coordinates of the matching area and the coordinates of f _t,i in x _t , if all in x The number of templates that can find matching regions in _t+1 is N _t,2 , then the relative displacement set {s _t+1,j } (i=1,2,...,N _t,2 |t=1, 2, ...).

In one embodiment, the present invention also provides a method for obtaining an average displacement based on a motion salient point, wherein the step S1 includes:

S1.1. Based on the frame difference between the river surface images at time t and time t-1, obtain the motion saliency feature map at the current time;

S1.2. Based on the corner point detection method (such as the Harris operator), detect the key points in the motion saliency feature map, and obtain the motion salience points at time t, whose set is denoted as {ft _{, i} } (i=1, 2, . . . , N _{t, 1} | t=1, 2, . . . ).

In one embodiment, the step S2 includes:

S2.1. For the SIFT feature of the motion salient point in the motion salient feature map at each moment within a certain period of time, search for the SIFT of the motion salient point at time t-1 from the motion salient points at time t The points where the features match are used as matching points.

In one embodiment, denoising processing (for example, using Ransac algorithm) is performed on the matching points to remove incorrect matching points and retain correct matching points.

S2.2. Calculate the relative displacement of the matching points in the motion saliency feature map from time t-1 to time t. If the number of matching points that can be found in x _t is N _t,m , then each The set of relative displacements {s _{t, k} } (k=1, 2, ..., N _{t, m} |t = 1, 2, ...) of the motion salient points.

S2.3. Based on the relative displacement of the corresponding matching point at each moment within a certain period of time, obtain a histogram of relative displacement, and use the average value of the peak value in the histogram and the value of a certain range of areas near the peak value as a certain period of time the average displacement.

In one embodiment, the step S3 includes: obtaining the displacement of matching points or matching regions at many moments in a period of time, and then making a histogram of these displacements, which usually forms a single-peak graph, and we find the peak ( p), which is the area where the calculated displacement is most concentrated within a period of time. However, we still consider the contribution of displacements other than p to the total average displacement. We can take a range (±⊿p) around p, that is, take the interval [p-⊿p, p+⊿p], and calculate all The inter-frame displacements within this range are all added up and averaged, that is, the average displacement is the total average displacement, which helps to eliminate errors caused by some inter-frame matching errors in the subsequent template matching method.

FIG. 2 shows a histogram in an embodiment of the present invention, where the abscissa in the figure is the displacement in units of pixels, and the ordinate is the number of regions at a certain displacement. It can be seen from Figure 2 that when the displacement is about 27 pixels, the number of accumulated areas is the largest, so 27 is regarded as the peak value, and a range is taken around it, such as ±5 pixels, only for the range of [22, 32] The displacement is averaged to calculate the average displacement over a period of time. It can be seen from Figure 2 that some displacements are very large (such as those after 43), and we regard them as caused by mismatching during template matching, or noise.

In one embodiment, before the step S3, it also includes;

Based on the camera distance, camera angle and camera focal length, the scale calibration coefficient is obtained:

f _n =z/af

Among them, f _n is the scale calibration coefficient, z is the distance from the focal point of the camera lens to the water surface, α is the magnification from the imaging plane to the image plane, and f is the focal length of the camera lens.

In one embodiment, the calculation expression for obtaining the average flow velocity within a certain period of time based on the scale calibration coefficient and the average displacement at each moment within a certain period of time and the time between frames is:

Among them, fn is the scale calibration coefficient, is the average displacement, Δt is the time between frames, and v is the average river surface velocity.

Fig. 3 shows a kind of structural block diagram of the system of measuring river surface average velocity of the present invention, comprises:

A motion salience detection device, used to obtain a motion salience point or a motion salience area of the river surface image at the current moment based on the river surface image at the current moment and the previous moment;

An average displacement detection device, connected to the motion salience detection device, based on the motion salience point or motion salience area at each moment within a certain period of time, to obtain the average displacement within a certain period of time; and

The average flow velocity detection device is connected with the average displacement detection device, and the average flow velocity detection device is used to obtain the average flow velocity within a certain period of time based on the scale calibration coefficient, the average displacement at each moment within a certain period of time, and the time between frames.

In one embodiment, the motion salience detection device includes:

A feature map generation module, used to obtain a motion saliency feature map at the current moment based on the frame difference between the current moment and the river surface image at the previous moment; and

The saliency detection module is connected with the feature map generation module, and the salience detection module obtains the motion salience area of the river surface image at the current moment based on the motion saliency feature map at the current moment.

In one embodiment, the average displacement detection device includes:

A matching area checking module, connected with the feature map generation module and the saliency detection module, the matching area checking module is used to search the saliency feature map at the current moment and each motion saliency area matching at the previous moment matching area;

A relative displacement calculation module, connected to the matching area inspection module, the relative displacement calculation module is used to calculate the relative displacement of the matching area in the motion salience feature map from the previous moment to the current moment; and

The average displacement calculation module obtains a histogram of relative displacement based on the relative displacement of the corresponding matching area at each moment within a certain period of time, and the average value of the peak value in the histogram and a certain range of values around the peak value is used as the Average displacement over time.

In one embodiment, the image of the river surface is taken with the main optical axis of the camera perpendicular to the water surface and the lens aimed at the river in combination with a level.

In one embodiment, the distance from the focal point of the camera lens to the water surface is obtained through a microwave range finder.

Finally, the method of the present application is only a preferred embodiment, and is not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims (10)

1. A method for measuring the average velocity of a river surface, characterized in that, comprising: S1. Based on the river surface image at the current moment and the previous moment, obtain the salient point or region of motion in the river surface image at the current moment; S2. Obtain an average displacement within a certain period of time based on the significant points of movement or the significant regions of movement at each moment within a certain period of time; and S3. Obtain an average flow velocity within a certain period of time based on the scale calibration coefficient, the average displacement within the certain period of time, and the time between frames. 2. the method for measuring river surface average velocity as claimed in claim 1, is characterized in that, described step S1 comprises: S1.1. Obtain the motion saliency feature map at the current moment based on the frame difference between the river surface image at the current moment and the previous moment; and S1.2. Based on the motion saliency feature map at the current moment, obtain the motion saliency region of the river surface image at the current moment. 3. the method for measuring river surface average velocity as claimed in claim 2, is characterized in that, described step S1.2 comprises: S1.2.1. Binarize the motion saliency feature map at the current moment to obtain a binary map; S1.2.2. Select several connected domains on the binary image, any one of which is a rectangle with a length or width of 20-100 pixels; and S1.2.3. Using the connected domain as a mask, find the position corresponding to the connected domain in the motion saliency feature map at the current moment, and use it as the motion saliency region. 4. the method for measuring river surface average velocity as claimed in claim 3, is characterized in that, described step S2 comprises: S2.1. Search for a matching region that matches each motion salient region at the previous moment in the salient feature map at the current moment; S2.2. Calculate the relative displacement of the matching region in the motion saliency feature map from the previous moment to the current moment; and S2.3. Obtain a histogram of relative displacement based on the relative displacement of the corresponding matching area at each moment within a certain period of time, and use the average value of the peak value in the histogram and a certain range of values near the peak value as the certain Average displacement over time. 5. the method for measuring river surface average velocity as claimed in claim 1, is characterized in that, described step S1 comprises: S1.1. Obtain the motion saliency feature map at the current moment based on the frame difference between the river surface image at the current moment and the previous moment; S1.2. Based on a corner point detection method, detect key points in the motion saliency feature map, and obtain the motion salience point at this moment. 6. the method for measuring river surface average velocity as claimed in claim 5, is characterized in that, described step S2 comprises: S2.1. For the SIFT feature of the motion salient point in the motion salient feature map at each moment within a certain period of time, search for the SIFT feature of the motion salient point at the previous moment from the motion salient points at the current moment Matching points, as matching points; S2.2. Calculate the relative displacement of the matching point in the motion saliency feature map from the previous moment to the current moment; and S2.3. Based on the relative displacement of the corresponding matching point at each moment within a certain period of time, obtain a histogram of relative displacement, and use the average value of the peak value in the histogram and the value of a certain range of areas near the peak value as a certain period of time the average displacement. 7. the method for measuring river surface average velocity as claimed in claim 1, is characterized in that, also comprises before described step S3: The scale calibration coefficient is obtained based on the camera distance, camera angle and camera focal length. 8. A system for measuring the average velocity of a river surface, comprising: A motion salience detection device, used to obtain a motion salience point or a motion salience area of the river surface image at the current moment based on the river surface image at the current moment and the previous moment; An average displacement detection device, connected to the motion salience detection device, based on the motion salience point or motion salience area at each moment within a certain period of time, to obtain the average displacement within a certain period of time; and The average flow velocity detection device is connected with the average displacement detection device, and the average flow velocity detection device is used to obtain the average flow velocity within a certain period of time based on the scale calibration coefficient, the average displacement at each moment within a certain period of time, and the time between frames. 9. The system for measuring the average velocity of the river surface as claimed in claim 8, wherein the motion significance detection device comprises: A feature map generation module, used to obtain a motion saliency feature map at the current moment based on the frame difference between the current moment and the river surface image at the previous moment; and The saliency detection module is connected with the feature map generation module, and the salience detection module obtains the motion salience area of the river surface image at the current moment based on the motion saliency feature map at the current moment. 10. the system of measuring river surface average flow velocity as claimed in claim 9, is characterized in that, described average displacement detection device comprises: A matching area checking module, connected with the feature map generation module and the saliency detection module, the matching area checking module is used to search the saliency feature map at the current moment and each motion saliency area matching at the previous moment matching area; A relative displacement calculation module, connected to the matching area inspection module, the relative displacement calculation module is used to calculate the relative displacement of the matching area in the motion salience feature map from the previous moment to the current moment; and The average displacement calculation module obtains a histogram of relative displacement based on the relative displacement of the corresponding matching area at each moment within a certain period of time, and the average value of the peak value in the histogram and a certain range of values around the peak value is used as the Average displacement over time.