CN108471530B - Method and apparatus for detecting video - Google Patents

Abstract

The embodiment of the application discloses a method for detecting video. One embodiment of the method comprises: acquiring a video to be detected; carrying out interlaced detection on a video to be detected, and determining the interlaced type of the video to be detected; in response to the fact that the interlaced type of the video to be detected is the interlaced type, sequentially detecting top and bottom fields of the video to be detected, and determining the field priority sequence of the video to be detected; and generating a detection result of the video to be detected, wherein the detection result of the video to be detected comprises the interlaced type and the field priority of the video to be detected. The embodiment can quickly generate the detection result of the video.

Description

Method and apparatus for detecting video

technical field

The embodiments of the present application relate to the field of computer technologies, and in particular, to methods and devices for detecting videos.

Background technique

At present, the video format types of videos such as radio, television and movies are divided into interlaced type and progressive type. In the interlaced type video, each frame of video image is divided into two fields according to odd-numbered lines and even-numbered lines, which are called top field and bottom field. In the early SD era, in order to save bandwidth, video was usually transmitted in units of fields, that is, one field of each frame of video image was dropped and another field was transmitted, and early analog TVs also played video according to fields. Therefore, video in the SD era is usually interlaced video. In today's high-definition era, digital TV has become popular, and digital TV plays video by frame. Therefore, for early interlaced video, it is necessary to perform de-interlacing processing to convert interlaced video into progressive video for playback.

However, when the video is deinterlaced, it is necessary to determine the top and bottom field order of the video to sort the processed video images according to the top and bottom field order, so as to ensure that the picture sequence displayed in the processed video does not appear. disorder.

SUMMARY OF THE INVENTION

The embodiments of the present application provide a method and device for detecting video.

In a first aspect, an embodiment of the present application provides a method for detecting a video, including: acquiring a video to be detected; performing interlace detection on the video to be detected, and determining the interlace type of the video to be detected; The progressive interlaced type is an interlaced type, and the top and bottom field sequence detection is performed on the video to be detected to determine the field priority of the video to be detected; the detection result of the video to be detected is generated, wherein the detection result of the video to be detected includes the video to be detected. Type and field precedence.

In some embodiments, performing interlace detection on the video to be detected and determining the interlace type of the video to be detected includes: for each pixel in each frame of the video to be detected in the video to be detected, calculating the horizontal The amount of change in the direction, the field frequency value of the pixel, the frame frequency value of the pixel and the time change of the pixel, the change of the pixel in the horizontal direction, the field frequency of the pixel value, the frame frequency value of the pixel point, and the time change of the pixel point are analyzed to determine whether the pixel point is a drawing point; count the drawing point ratio in each frame of the video image to be detected in the video to be detected, and obtain Statistical results; based on the statistical results, determine the line-by-line type of the video to be detected.

In some embodiments, the change amount of the pixel point in the horizontal direction, the field frequency value of the pixel point, the frame frequency value of the pixel point, and the change amount of the pixel point in time are analyzed to determine the pixel point. Whether it is a wire drawing point includes: if the pixel point satisfies the first condition, then determining that the pixel point is a wire drawing point, wherein the first condition includes: the amount of change of the pixel point in the horizontal direction is greater than the first threshold, and the pixel point is at time. The amount of change on the pixel is greater than the second threshold value, and the frame frequency value of the pixel point is greater than the sum of the field frequency value and the third threshold value.

In some embodiments, counting the ratio of drawing points in each frame of the video image to be detected in the video to be detected, to obtain the statistical result, includes: for each frame of the video image to be detected in the video to be detected, calculating the percentage of the video image to be detected in the video image to be detected. The ratio of the number of drawing points to the number of pixel points that satisfy the second condition, wherein the second condition includes: the change amount of the pixel point in the horizontal direction is greater than the first threshold, and the change amount of the pixel point in time is greater than the second Threshold; compare the obtained ratio with the fourth threshold; if the obtained ratio is greater than the fourth threshold, then determine that the interlaced type of the video image to be detected is the interlaced type; if the obtained ratio is not greater than the fourth threshold, Then it is determined that the progressive interlaced type of the video image to be detected is the progressive type.

In some embodiments, performing top-bottom field sequence detection on the video to be detected, and determining the field priority of the video to be detected, includes: for every two adjacent video images to be detected in the video to be detected, determining the adjacent video images of the two frames. The video image to be detected is divided into four fields; the missing field is filled with the average value of the pixel points of the upper and lower lines to obtain four frames of images; the difference of the pixel points of the corresponding positions in the two frame images of the four frames of images is calculated. Sum of absolute values: analyze the sum of absolute values of the differences of the pixel points at the corresponding positions in the two frames of images, and determine the field priority order of the video to be detected.

In some embodiments, calculating the sum of absolute values of differences of pixel points at corresponding positions in two frames of images in the four frames of images includes: dividing the four frames of images into two pairs of images; The sum of the absolute values of the differences of the pixel points.

In some embodiments, the first pair of images in the two pairs of images includes: a bottom field and a top field mosaic generated after filling the previous video image to be detected in the two adjacent frames of video images to be detected. formed image, the next frame to be detected video image in the two adjacent video images to be detected is divided into the top field and the bottom field generated after filling; the second pair of images in the two pairs of images Including: an image composed of a top field and a bottom field generated after filling of the previous frame of the video image to be detected in the two adjacent video images to be detected, and an image of the two adjacent video images to be detected. The bottom field of the next frame of the video image to be detected is divided into an image composed of the top field generated after filling.

In some embodiments, analyzing the sum of the absolute values of the differences of the pixel points at the corresponding positions in the two frames of images in the four frames of images, and determining the field priority of the video to be detected, includes: The sum of the absolute values of the differences of the pixel points of the position is compared with the sum of the absolute values of the differences of the pixel points of the corresponding positions in the second pair of images; if the absolute value of the difference of the pixel points of the corresponding positions in the first pair of images is If the sum of the values is greater than the sum of the absolute values of the differences of the pixel points at the corresponding positions in the second pair of images, it is determined that the field priority of the video to be detected is the bottom field priority; if the difference between the pixel points at the corresponding positions in the first pair of images is If the sum of the absolute values of the values is not greater than the sum of the absolute values of the differences of the pixel points at the corresponding positions in the second pair of images, it is determined that the field priority order of the video to be detected is the top field priority.

In some embodiments, the method further includes: in response to determining that the progressive interlaced type of the video to be detected is the progressive type, generating a detection result of the video to be detected, wherein the detection result of the video to be detected includes the progressive interlaced type of the video to be detected type.

In some embodiments, the method further includes: outputting the detection result of the video to be detected.

In a second aspect, an embodiment of the present application provides an apparatus for detecting video, including: an acquisition unit, configured to acquire the video to be detected; a first detection unit, configured to perform interlace detection on the video to be detected, and determine the video to be detected. Detecting the progressive interlaced type of the video; a second detection unit configured to perform top and bottom field sequence detection on the video to be detected in response to determining that the progressive interlaced type of the video to be detected is the interlaced type, to determine the field priority of the video to be detected; the generating unit , configured to generate a detection result of the video to be detected, wherein the detection result of the video to be detected includes the interlace type and field priority of the video to be detected.

In a third aspect, an embodiment of the present application provides an electronic device, the electronic device includes: one or more processors; a storage device for storing one or more programs; when one or more programs are stored by one or more The processor executes such that the one or more processors implement a method as described in any implementation of the first aspect.

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

The method and device for detecting video provided by the embodiments of the present application, by performing interlace detection on the acquired video to be detected, so as to determine the interlace type of the video to be detected; when it is determined that the interlace type of the video to be detected is the interlace type In the case of , the top and bottom field sequence detection is performed on the video to be detected, so as to determine the field priority of the video to be detected; finally, the detection result of the video to be detected is generated. Thus, the detection result of the video can be quickly generated.

Description of drawings

Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

FIG. 1 is an exemplary system architecture diagram to which embodiments of the present application may be applied;

Figure 2 is a flowchart of one embodiment of a method for detecting video according to the present application;

Figure 3 is a flowchart of yet another embodiment of a method for detecting video according to the present application;

4 is a schematic diagram of the distribution of pixels in a frame of video images to be detected;

5 is a schematic diagram of the distribution of pixels in four fields into which two adjacent video images to be detected are divided;

6 is a schematic diagram of the distribution of pixels of four frames of images with a bottom field that is filled with four fields;

FIG. 7 is a schematic diagram of the distribution of pixels of four frames of images with top field priority filled into four fields;

FIG. 8 is a schematic structural diagram of a computer system suitable for implementing the electronic device according to the embodiment of the present application.

Detailed ways

The present application will be further described in 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 related invention, but not to limit the invention. In addition, it should be noted that, for the convenience of description, only the parts related to the related invention are shown in the drawings.

It should be noted that the embodiments in the present application and the features of the embodiments may be combined with each other in the case of no conflict. The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

FIG. 1 illustrates an exemplary system architecture 100 to which embodiments of the present method for detecting video may be applied.

As shown in FIG. 1 , the system architecture 100 may include a cloud server 101 , an electronic device 102 , a digital television 103 , and networks 104 and 105 . The network 104 is a medium used to provide a communication link between the cloud server 101 and the electronic device 102 . The network 105 is the medium used to provide the communication link between the electronic device 102 and the digital television 103 . The networks 104, 105 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

The cloud server 101 can interact with the electronic device 102 through the network 104 to receive or send messages and the like. The electronic device 102 can interact with the digital television 103 through the network 105 to receive or send messages and the like. The cloud server 101 may be a server for storing a large amount of interlaced video and/or progressive video. The digital television 103 may be a television for playing progressive video or progressive video converted from interlaced video after de-interlacing processing.

The electronic device 102 can provide various services. For example, the electronic device 102 can analyze and process the acquired video and other data to be detected, and feed back the processing result (eg, the detection result of the video to be detected) to the digital TV 103 .

It should be noted that the electronic device 102 may be hardware or software. When the electronic device 102 is hardware, it can be various electronic devices, including but not limited to ASIC (Application Specific Integrated Circuit) chips, FPGA (Field Programmable Gate Array, field programmable gate array), OTT (Over The Top, Internet TV) boxes, IPTV (Interactive Personality Television) boxes and servers, etc. When the electronic device 102 is software, it can be installed in the electronic devices listed above. It can be implemented as multiple software or software modules (eg, to provide distributed services), or as a single software or software module. There is no specific limitation here.

It should be noted that, the method for detecting video provided by the embodiment of the present application is generally performed by the electronic device 102 .

It should be understood that the numbers of cloud servers, electronic devices, digital TVs and networks in FIG. 1 are merely illustrative. There can be any number of cloud servers, electronic devices, digital TVs and networks according to implementation needs.

With continued reference to FIG. 2, a flow 200 of one embodiment of a method for detecting video according to the present application is shown. The method for detecting video includes the following steps:

Step 201, acquiring the video to be detected.

In this embodiment, the execution body of the method for detecting video (for example, the electronic device 102 shown in FIG. 1 ) may be obtained from a cloud server (for example, the cloud server 101 shown in FIG. 1 ) through a wired connection or a wireless connection Video to be detected. Among them, a large amount of videos can be stored in the cloud server, and different videos can be distinguished by different identifiers.

In practice, the user can initiate a video playback request through a digital TV (for example, the digital TV 103 shown in FIG. 1 ), wherein the video playback request can include the identifier of the video the user wants to watch, and the cloud server can The identification of the video finds the video that the user wants to watch from the massive video stored in the video, and then sends it to the above-mentioned executive body. Here, the video the user wants to watch is the video to be detected.

Step 202: Perform interlace detection on the video to be detected, and determine the interlace type of the video to be detected.

In this embodiment, based on the to-be-detected video acquired in step 201, the above-mentioned execution body may perform line-by-line detection on the to-be-detected video, thereby determining the line-by-line type of the to-be-detected video.

In this embodiment, the video can be classified into an interlaced type and a progressive type according to the video format type. Usually, interlaced type video is obtained by interlacing. Interlacing is to divide each frame of video image in the video into two fields, that is, scan one line from left to right, and scan one line from top to bottom until the last line. The field including all odd-numbered lines in one frame of video image is the top field, and the field including all even-numbered lines in one frame of video image is the bottom field. Progressive type video is obtained by progressive scanning. Progressive scanning means that each frame of video image in the video is scanned line by line from left to right, top to bottom, until all lines are scanned.

In some optional implementations of this embodiment, the video stored in the cloud server may include attribute information of the video, and the attribute information of the video may include the video's line-by-line type. Therefore, the above-mentioned execution body may determine the progressive interlace type of the video to be detected according to the attribute information of the video to be detected included in the video to be detected. If the attribute information of the video to be detected indicates that the video to be detected is a progressive video, then it is determined that the progressive interlaced type of the video to be detected is progressive; if the attribute information of the video to be detected indicates that the video to be detected is an interlaced video, then It is determined that the progressive interlaced type of the video to be detected is the interlaced type.

Step 203, in response to determining that the interlaced type of the video to be detected is the interlaced type, perform top and bottom field sequence detection on the video to be detected, and determine the field priority of the video to be detected.

In this embodiment, when it is determined that the interlaced type of the video to be detected is the interlaced type, the above-mentioned execution body can perform top and bottom field sequence detection of the video to be detected, thereby determining the field priority of the video to be detected.

In this embodiment, in order to save bandwidth, each frame of video image of the interlaced type video loses one field. Therefore, each frame of the interlaced video image in the video of the interlaced type is reserved from two adjacent video images. Combining the two. For example, in two adjacent frames of video images, the bottom field of the previous frame of video image is reserved, and the top field of the next frame of video image is reserved, and the bottom field of the previous frame of video image and the top field of the next frame of video image are combined to obtain A frame of interlaced video images, and the field priority order of the interlaced video images is bottom field priority. For another example, the previous frame of video images in two adjacent video images retains the top field, the next frame of video images retains the bottom field, and the top field of the previous frame of video image and the bottom field of the next frame of video image are combined, A frame of interlaced video image is obtained, and the field priority order of the interlaced video image is top field priority.

In some optional implementations of this embodiment, the video stored in the cloud server may include attribute information of the video, and the attribute information of the video may include the field priority of the video. Therefore, the above-mentioned executive body can determine the field priority order of the video to be detected according to the attribute information of the video to be detected included in the video to be detected. If the attribute information of the video to be detected indicates that the video to be detected is a bottom-field priority video, then determine that the field priority of the video to be detected is the bottom-field priority; if the attribute information of the video to be detected indicates that the video to be detected is a top-field priority video, Then it is determined that the field priority order of the video to be detected is the top field priority.

Step 204, generating a detection result of the video to be detected.

In this embodiment, based on the progressive interlace type of the video to be detected determined in step 202 and the field priority of the video to be detected determined in step 203, the above-mentioned execution body can generate a detection result of the video to be detected. The detection result of the video to be detected may include the interlace type and field priority of the video to be detected. Here, the detection results of the video to be detected can include two types, one is: the progressive interlaced type of the video to be detected is the interlaced type, and the field priority is bottom field priority; the other is: the progressive interlaced type of the video to be detected is Interlaced type, and the field priority is top field priority.

In some optional implementations of this embodiment, in a case where it is determined that the progressive interlaced type of the video to be detected is the progressive type, the above-mentioned execution body may generate a detection result of the video to be detected. The detection result of the video to be detected may include a line-by-line type of the video to be detected. Here, the detection result of the video to be detected may include one, that is, the progressive interlaced type of the video to be detected is the progressive type.

In some optional implementation manners of this embodiment, after generating the detection result of the video to be detected, the above-mentioned execution body may output the detection result of the video to be detected. Generally, the above-mentioned executive body can send the video to be detected and the detection result of the video to be detected to the digital TV at the same time, and the digital TV can play the video to be detected according to the detection result of the video to be detected. Specifically, when the detection result of the video to be detected indicates that the progressive type of the video to be detected is progressive, the digital TV can directly play the video to be detected; when the detection result of the video to be detected indicates that the progressive type of the video to be detected is interlaced Type, the digital TV can de-interlace each frame of the video image to be detected in the video to be detected, and then sort the processed video images according to the field priority in the detection result of the video to be detected to obtain the processed video, and finally Play the processed video.

The method and device for detecting video provided by the embodiments of the present application, by performing interlace detection on the acquired video to be detected, so as to determine the interlace type of the video to be detected; when it is determined that the interlace type of the video to be detected is the interlace type In the case of , the top and bottom field sequence detection is performed on the video to be detected, so as to determine the field priority of the video to be detected; finally, the detection result of the video to be detected is generated. Thus, the detection result of the video can be quickly generated.

With further reference to Figure 3, a flow 300 of yet another embodiment of a method for detecting video is shown. The method for detecting video includes the following steps:

Step 301, acquiring the video to be detected.

In this embodiment, the execution body of the method for detecting video (for example, the electronic device 102 shown in FIG. 1 ) may be obtained from a cloud server (for example, the cloud server 101 shown in FIG. 1 ) through a wired connection or a wireless connection Video to be detected.

Step 302, for each pixel in the video image to be detected for each frame in the video to be detected, calculate the variation of the pixel in the horizontal direction, the field frequency value of the pixel, the frame frequency value of the pixel and The amount of change in time for this pixel.

In this embodiment, for each pixel point in each frame of the video image to be detected in the video to be detected, the above-mentioned execution body can calculate the amount of change of the pixel point in the horizontal direction, the field frequency value of the pixel point, the The frame frequency value of the pixel point and the amount of time change of the pixel point.

Taking FIG. 4 as an example, it shows a schematic diagram of the distribution of pixel points in a frame of video image to be detected. The video image to be detected has 5×5 pixels, the first 5 is the number of horizontal pixels, the second 5 is the number of vertical pixels, and a “●” in FIG. 4 represents a pixel.

Here, the horizontal change amount hor_diff of the pixels in the third row and the third column in Figure 4 can be calculated by the following formula:

hor_diff=(|c1-c2|+|c2-c3|+|c3-c4|+|c4-c5|)/4;

Among them, c1 is the pixel value of the pixel point in the third row and the first column in FIG. 4 , c2 is the pixel value of the pixel point in the third row and the second column in FIG. 4 , and c3 is the third row in FIG. 4 . The pixel value of the pixel point in the 3rd column, c4 is the pixel value of the pixel point in the 3rd row and the 4th column in FIG. 4 , and c5 is the pixel value of the pixel point in the 3rd row and the 5th column in FIG. 4 .

Here, the field frequency value field_freq of the pixel point in the 3rd row and 3rd column in FIG. 4 can be calculated by the following formula:

field_freq=|2×c3-a3-e3|;

Among them, a3 is the pixel value of the pixel point in the first row and the third column in FIG. 4 , and e3 is the pixel value of the pixel point in the fifth row and the third column in FIG. 4 .

Here, the frame frequency value frame_freq of the pixel point in the 3rd row and 3rd column in FIG. 4 can be calculated by the following formula:

frame_freq=|2×c3-b3-d3|;

Wherein, b3 is the pixel value of the pixel point in the second row and the third column in FIG. 4 , and d3 is the pixel value of the pixel point in the fourth row and the third column in FIG. 4 .

Here, the temporal variation temp_diff of the pixels in the 3rd row and 3rd column in Figure 4 can be calculated by the following formula:

temp_diff=|last_c3-c3|;

Wherein, last_c3 is the pixel value of the pixel point in the third row and the third column in the video image to be detected in the previous frame of FIG. 4 .

It should be noted that the pixel value of the pixel point here may be the value of Y in YUV. Among them, YUV is a color coding method adopted by the European television system, "Y" represents the brightness (Luminance or Luma), that is, the grayscale value; and "U" and "V" represent the color Degree (Chrominance or Chroma) is used to describe the color and saturation of the image and is used to specify the color of the pixel.

Step 303, analyze the variation of the pixel in the horizontal direction, the field frequency value of the pixel, the frame frequency value of the pixel and the temporal variation of the pixel to determine whether the pixel is a wire drawing point.

In this embodiment, based on the variation of the pixel in the horizontal direction, the field frequency value of the pixel, the frame frequency value of the pixel and the temporal variation of the pixel calculated in step 302, The above-mentioned executive body can analyze the change amount of the pixel point in the horizontal direction, the field frequency value of the pixel point, the frame frequency value of the pixel point and the time change amount of the pixel point, so as to determine whether the pixel point is Is the drawing point.

In some optional implementations of this embodiment, the above-mentioned execution body may determine whether the pixel point is a wire drawing point through the following analysis method: if the pixel point satisfies the first condition, it is determined that the pixel point is a wire drawing point, wherein, The first condition may include: the horizontal change of the pixel is greater than the first threshold, the temporal change of the pixel is greater than the second threshold, and the frame frequency value of the pixel is greater than the sum of the field frequency and the third threshold.

Continuing to take Figure 4 as an example, if the pixel in the 3rd row and 3rd column in Figure 4 satisfies the following three conditions at the same time, the pixel is a drawing point; otherwise, it is not a drawing point:

hor_diff > edge_thr;

temp_diff > move_thr;

frame_freq>field_freq+freq_thr;

Among them, edge_thr is the first threshold, and its value range is usually around 10, move_thr is the second threshold, and freq_thr is the third threshold.

Here, the second threshold move_thr can be calculated by the following formula:

move_thr=max(frame_freq/4,5).

Here, the third threshold freq_thr can be calculated by the following formula:

freq_thr=frame_freq/4.

Step 304 , count the ratio of drawing points in each frame of the video image to be detected in the video to be detected, and obtain a statistical result.

In this embodiment, the above-mentioned execution body can count the proportion of the wire drawing points in each frame of the video image to be detected in the video to be detected, so as to obtain the statistical result.

Here, the first parameter fila_cnt can be preset, and its initial value is set to 0. For each frame of the video image to be detected in the video to be detected, it can be determined one by one whether the pixel is a wire drawing point. If it is determined that a pixel is a wire drawing point , increase the first parameter fila_cnt by 1, and continue to determine whether the next pixel is a drawing point until all pixels have been determined. At this time, the value of the first parameter fila_cnt is the number of drawing points in the video image to be detected. .

In some optional implementations of this embodiment, for each frame of the to-be-detected video image in the to-be-detected video, the above-mentioned execution body may first calculate the number of drawing points in the to-be-detected video image and the pixels that satisfy the second condition The ratio of the number of points; then compare the obtained ratio with the fourth threshold, if the obtained ratio is greater than the fourth threshold, then determine that the interlaced type of the video image to be detected is the interlaced type, if the obtained ratio is not If it is greater than the fourth threshold, it is determined that the progressive interlaced type of the video image to be detected is the progressive type. Wherein, the second condition may include: the change amount of the pixel point in the horizontal direction is greater than the first threshold, and the change amount of the pixel point in time is greater than the second threshold value.

Continuing to take FIG. 4 as an example, if the pixel in the third row and the third column in FIG. 4 satisfies the following two conditions at the same time, the pixel is a pixel that satisfies the second condition; otherwise, it does not satisfy the second condition. pixel:

hor_diff > edge_thr;

temp_diff>move_thr.

Here, the second parameter cnt can be preset, and its initial value is set to 0. For each frame of the video image to be detected in the video to be detected, it can be determined one by one whether the pixels meet the second condition, if it is determined that a pixel meets the first The second condition is to increase the second parameter cnt by 1, and continue to determine whether the next pixel satisfies the second condition until all pixels are determined. At this time, the value of the second parameter cnt is the video image to be detected that satisfies the second condition. The number of pixels for the second condition.

Here, the ratio ratio between the number of drawing points in the video image to be detected and the number of pixels satisfying the second condition can be calculated by the following formula:

ratio=fila_cnt/cnt.

Here, a fourth threshold ratio_thr can be preset, and its value range is usually between 0 and 1, and the ratio is compared with the fourth threshold ratio_thr. If ratio>ratio_thr, it is determined that the line-by-line type of the video image to be detected is Interlaced type, otherwise, it is determined that the video image to be detected is of progressive type.

Step 305 , based on the statistical result, determine the line-by-line type of the video to be detected.

In this embodiment, based on the statistical result obtained in step 304, the above-mentioned execution subject may determine the progressive interlace type of the video to be detected.

In practice, since the determination result of one frame of video images to be detected may be inaccurate, the determination results of multiple frames of video images to be detected may be accumulated to determine the type of interlaced video to be detected. For example, if the proportion of to-be-detected video images belonging to the interlaced type in the video to be detected is greater than a certain value, then it is determined that the progressive interlaced type of the video to be detected is the interlaced type; otherwise, it is determined that the progressive interlaced type of the video to be detected is the progressive type. For another example, the number of drawing points in each frame of the video image to be detected in the video to be detected is accumulated, and the number of pixels that satisfy the second condition in each frame of the video image to be detected in the video to be detected is accumulated, and the accumulated number of drawing points in each frame of the video image to be detected is accumulated. The ratio of the number to the accumulated number of pixels satisfying the second condition is compared with the fourth threshold, and if the obtained ratio is greater than the fourth threshold, it is determined that the interlaced type of the video to be detected is the interlaced type, and if the obtained ratio is greater than the fourth threshold If the ratio is not greater than the fourth threshold, it is determined that the progressive interlaced type of the video to be detected is the progressive type.

Step 306 , in response to determining that the interlaced type of the video to be detected is the interlaced type, for every two adjacent video images to be detected in the video to be detected, divide the adjacent video images to be detected into four fields.

In this embodiment, when it is determined that the interlaced type of the video to be detected is the interlaced type, for every two adjacent frames of the video image to be detected in the video to be detected, the execution body may The video image to be detected is divided into four fields.

Here, since the interlaced video image is composed of the bottom field of one frame of video image and the top field of another frame of video image in two adjacent frames of images, each frame of interlaced video image can be divided into two fields, One field belongs to one frame of video image in two adjacent frames of images, and the other field belongs to another frame of video image in the two adjacent frames of images.

Taking FIG. 5 as an example, it shows a schematic diagram of the distribution of pixels in four fields divided into two adjacent video images to be detected. Wherein, each dashed frame frame is a frame of video image to be detected into two fields, each field includes 3 rows of pixels, a “■” in FIG. 5 represents a row of pixels.

Step 307: Fill the missing field with the average value of the upper and lower rows of pixels to obtain four frames of images.

In this embodiment, based on the four fields divided into step 306, the above-mentioned execution subject can fill in the missing fields by using the average value of the upper and lower rows of pixels, thereby obtaining four frames of images.

Taking FIG. 6 as an example, it shows a schematic diagram of pixel point distribution of four frames of images filled with four fields and having a bottom field priority. Among them, each frame of video image includes 6 lines of pixels, a "■" in Figure 6 represents a line of pixels in the reserved field, and a "□" represents a line of pixels in the filled field, and the image marked with 1 is two frames. In the adjacent video images to be detected, the image of the bottom field divided into the video image to be detected of the previous frame and the top field generated after filling, the image marked with 2 is two adjacent video images to be detected. The image of the top field and the bottom field generated after filling the previous frame of the video image to be detected is divided into, and the image marked with 3 is the next frame of the video image to be detected in the two adjacent video images to be detected. The image formed by the divided bottom field and the top field generated after filling, the image marked with 4 is the top field and the filling divided into the next frame of the video image to be detected in the two adjacent video images to be detected. Post-generated bottom field stitched image.

Taking FIG. 7 as an example, it shows a schematic diagram of the pixel point distribution of the top-field priority four-frame image filled with four fields. Among them, each frame of video image includes 6 lines of pixels, a "■" in Figure 7 represents a line of pixels in the reserved field, and a "□" represents a line of pixels in the filled field, and the image marked with 1 is two frames. In the adjacent video images to be detected, the image of the bottom field divided into the video image to be detected of the previous frame and the top field generated after filling, the image marked with 2 is two adjacent video images to be detected. The image of the top field and the bottom field generated after filling the previous frame of the video image to be detected is divided into, and the image marked with 3 is the next frame of the video image to be detected in the two adjacent video images to be detected. The image that the bottom field is divided into and the top field generated after filling, the image marked with 4 is the top field and the filling that the next frame of the video image to be detected is divided into two adjacent video images to be detected. Post-generated bottom field stitched image.

It should be noted that, in FIG. 6 and FIG. 7 , no matter how the generated four frames of images are sorted, the images with the same label are the same frame of images, for example, the image with the label of 1 in FIG. 6 is two adjacent frames of video images to be detected. The image that the bottom field and the top field generated after filling the previous frame of the video image to be detected are spliced together, and the image labeled 1 in FIG. An image composed of the bottom field divided into the video image to be detected and the top field generated after filling.

Step 308: Calculate the sum of the absolute values of the differences of the pixel points at the corresponding positions in the two frames of images in the four frames of images.

In this embodiment, based on the four frames of images obtained in step 307, the above-mentioned execution subject may calculate the sum of the absolute values of the difference values of the pixel points at the corresponding positions in the two frames of images in the four frames of images.

In some optional implementations of this embodiment, the above-mentioned execution body may firstly divide the four frames of images into two pairs of images; and then calculate the sum of the absolute values of the differences of pixel points at corresponding positions in each pair of images. For example, the first pair of images in the two pairs of images may include: an image composed of a bottom field and a top field generated after filling the two adjacent frames of the video images to be detected that are divided into the previous frame of the video image to be detected. , the image that the next frame to be detected video image in the two adjacent video images to be detected is divided into the top field and the bottom field generated after filling; The second pair of images in the two pairs of images can include: In the two adjacent frames of video images to be detected, the top field of the previous frame of the video image to be detected is divided into an image formed by the bottom field after filling, and the back field of the two adjacent frames of video images to be detected An image composed of a bottom field divided into a frame of video image to be detected and a top field generated after filling.

Continuing to take FIG. 6 or FIG. 7 as an example, the first pair of images may include an image numbered 1 and an image numbered 4, and the second pair of images may include an image numbered 2 and an image numbered 3. At the same time, the sum of the absolute values of the difference between the pixel points at the corresponding positions of the image labeled 1 and the image labeled 4 can be calculated by the following formula diff_abs_sum14;

Among them, i is a positive integer, and 1≤i≤N, N is the number of rows of the image, j is a positive integer, and 1≤j≤M, M is the number of columns of the image, f ¹ is the number of images in the image labeled 1 The pixel value of the pixel point, f _ij ¹ is the pixel value of the pixel point in the i-th row and the j-th column in the image labeled 1, f ⁴ is the pixel value of the pixel point in the image labeled 4, and f _ij ⁴ is The pixel value of the pixel in the i-th row and the j-th column in the image labeled 4.

Here, the sum of the absolute values of the difference between the pixel points at the corresponding positions of the image labeled 2 and the image labeled 3 can be calculated by the following formula diff_abs_sum23;

Wherein, f ² is the pixel value of the pixel in the image labeled 2, f _ij ² is the pixel value of the pixel in the ith row and jth column in the image labeled 2, and f ³ is the image labeled 3 The pixel value of the pixel in , f _ij ³ is the pixel value of the pixel in the i-th row and the j-th column in the image labeled 3.

It should be noted that the pixel value of the pixel point here may also be the value of Y in YUV.

Step 309 , analyze the sum of the absolute values of the differences of the pixel points at the corresponding positions in the two frames of images in the four frames of images, and determine the field priority of the video to be detected.

In this embodiment, based on the sum of the absolute values of the difference values of the pixel points at the corresponding positions in the two frames of images in the four frames of images calculated in step 308, the above-mentioned execution subject may The sum of the absolute values of the differences of the pixel points at the corresponding positions is analyzed to determine the field priority order of the video to be detected.

In some optional implementations of this embodiment, the above-mentioned execution body may calculate the sum of the absolute values of the difference values of the pixel points at the corresponding positions in the first pair of images and the difference value of the pixel points at the corresponding positions in the second pair of images If the sum of the absolute values of the differences of the pixel points at the corresponding positions in the first pair of images is greater than the sum of the absolute values of the differences of the pixel points at the corresponding positions in the second pair of images, it is determined to be The field priority order of the detected video is the bottom field priority; if the sum of the absolute values of the differences of the pixel points at the corresponding positions in the first pair of images is not greater than the sum of the absolute values of the differences of the pixel points at the corresponding positions in the second pair of images , then it is determined that the field priority order of the video to be detected is the top field priority.

Continuing to take FIG. 6 or FIG. 7 as an example, diff_abs_sum14 can be compared with diff_abs_sum23. If diff_abs_sum14>diff_abs_sum23, it is determined that the field priority of the video to be detected is the bottom field priority, otherwise, it is determined that the field priority of the video to be detected is the top field Field priority.

Step 310, generating a detection result of the video to be detected.

In this embodiment, the above-mentioned execution body may generate a detection result of the video to be detected. The detection result of the video to be detected may include the interlace type and field priority of the video to be detected. Here, the detection results of the video to be detected can include two types, one is: the progressive interlaced type of the video to be detected is the interlaced type, and the field priority is bottom field priority; the other is: the progressive interlaced type of the video to be detected is Interlaced type, and the field priority is top field priority.

As can be seen from FIG. 3 , compared with the embodiment corresponding to FIG. 2 , the flow 300 of the method for detecting video in this embodiment highlights the steps of determining the interlace type and field priority of the video to be detected. Therefore, the solution described in this embodiment improves the accuracy of the determined interlace type and field priority of the video to be detected.

Referring next to FIG. 8 , it shows a schematic structural diagram of a computer system 800 suitable for implementing the electronic device of the embodiment of the present application. The electronic device shown in FIG. 8 is only an example, and should not impose any limitations on the functions and scope of use of the embodiments of the present application.

As shown in FIG. 8, a computer system 800 includes a central processing unit (CPU) 801, which can be loaded into a random access memory (RAM) 803 according to a program stored in a read only memory (ROM) 802 or a program from a storage section 808 Instead, various appropriate actions and processes are performed. In the RAM 803, various programs and data necessary for the operation of the system 800 are also stored. The CPU 801 , the ROM 802 , and the RAM 803 are connected to each other through a bus 804 . An input/output (I/O) interface 805 is also connected to bus 804 .

The following components are connected to the I/O interface 805: an input section 806 including a keyboard, a mouse, etc.; an output section 807 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 808 including a hard disk, etc. ; and a communication section 809 including a network interface card such as a LAN card, a modem, and the like. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I/O interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is mounted on the drive 810 as needed so that a computer program read therefrom is installed into the storage section 808 as needed.

In particular, according to embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the method illustrated in the flowchart. In such an embodiment, the computer program may be downloaded and installed from the network via the communication portion 809, and/or installed from the removable medium 811. When the computer program is executed by the central processing unit (CPU) 801, the above-described functions defined in the method of the present application are performed. It should be noted that the computer-readable medium described in this application may be a computer-readable signal medium or a computer-readable medium, or any combination of the above two. The computer readable medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or a combination of any of the above. More specific examples of computer readable media may include, but are not limited to, electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable Read only memory (EPROM or flash memory), fiber optics, portable compact disk read only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. In this application, a computer-readable medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code therein. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable medium that can transmit, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any suitable medium including, but not limited to, wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Computer program code for performing the operations of the present application may be written in one or more programming languages, including object-oriented programming languages—such as Java, Smalltalk, C++, but also conventional Procedural programming language - such as "C" language or similar programming language. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (eg, using an Internet service provider through Internet connection).

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code that contains one or more logical functions for implementing the specified functions executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It is also noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented in dedicated hardware-based systems that perform the specified functions or operations , or can be implemented in a combination of dedicated hardware and computer instructions.

The units involved in the embodiments of the present application may be implemented in a software manner, and may also be implemented in a hardware manner. The described unit may also be provided in the processor, for example, it may be described as: a processor includes an acquisition unit, a first detection unit, a second detection unit and a generation unit. Wherein, the names of these units do not constitute a limitation on the unit itself under certain circumstances, for example, the acquisition unit may also be described as "a unit for acquiring the video to be detected".

As another aspect, the present application also provides a computer-readable medium. The computer-readable medium may be included in the electronic device described in the above embodiments; it may also exist alone without being assembled into the electronic device. middle. The above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by the electronic device, the electronic device: acquires the video to be detected; performs interlace detection on the video to be detected, and determines the content of the video to be detected. Progressive interlaced type; in response to determining that the progressive interlaced type of the video to be detected is the interlaced type, perform top and bottom field sequence detection on the video to be detected, and determine the field priority of the video to be detected; generate a detection result of the video to be detected, wherein the video to be detected is detected. The detection result includes the progressive interlace type and field priority of the video to be detected.

The above description is only a preferred embodiment of the present application and an illustration of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solution formed by the specific combination of the above technical features, and should also cover the above technical features or Other technical solutions formed by any combination of its equivalent features. For example, a technical solution is formed by replacing the above features with the technical features disclosed in this application (but not limited to) with similar functions.

Claims (10)

1. A method for detecting video, comprising:

acquiring a video to be detected;

carrying out interlaced detection on the video to be detected, and determining the interlaced type of the video to be detected;

in response to the fact that the interlaced type of the video to be detected is the interlaced type, sequentially detecting top and bottom fields of the video to be detected, and determining the field priority of the video to be detected;

generating a detection result of the video to be detected, wherein the detection result of the video to be detected comprises the interlaced type and the field priority of the video to be detected;

the interlace-by-interlace detection of the video to be detected and the determination of the interlace-by-interlace type of the video to be detected include:

for each pixel point in each frame of video image to be detected in the video to be detected, calculating the variation of the pixel point in the horizontal direction, the field frequency value of the pixel point, the frame frequency value of the pixel point and the variation of the pixel point in time, analyzing the variation of the pixel point in the horizontal direction, the field frequency value of the pixel point, the frame frequency value of the pixel point and the variation of the pixel point in time, and determining whether the pixel point is a wire drawing point;

counting the proportion of the wire drawing points in each frame of video image to be detected in the video to be detected to obtain a statistical result;

determining the interlacing type of the video to be detected based on the statistical result;

the performing top-bottom field sequence detection on the video to be detected and determining the field priority sequence of the video to be detected includes:

for every two adjacent frames of video images to be detected in the video to be detected, dividing the two adjacent frames of video images to be detected into four fields;

filling the missing field by using the average value of the upper and lower lines of pixel points to obtain four frames of images;

calculating the sum of absolute values of differences of pixel points at corresponding positions in two frames of images in the four frames of images;

and analyzing the sum of the absolute values of the differences of the pixel points at the corresponding positions in two frames of images in the four frames of images to determine the field priority of the video to be detected.

2. The method of claim 1, wherein analyzing the variation of the pixel point in the horizontal direction, the field frequency value of the pixel point, the frame frequency value of the pixel point, and the variation of the pixel point in time to determine whether the pixel point is a wire drawing point comprises:

if the pixel point meets a first condition, determining that the pixel point is a wire drawing point, wherein the first condition comprises: the variation of the pixel point in the horizontal direction is larger than a first threshold, the variation of the pixel point in the time direction is larger than a second threshold, and the frame frequency value of the pixel point is larger than the sum of the field frequency value and a third threshold.

3. The method according to claim 2, wherein the step of counting the proportion of the wire drawing points in each frame of the video image to be detected in the video to be detected to obtain a statistical result comprises:

for each frame of video image to be detected in the video to be detected, calculating the ratio of the number of the wire drawing points in the video image to be detected to the number of pixel points meeting a second condition, wherein the second condition comprises the following steps: the variation of the pixel points in the horizontal direction is larger than a first threshold, and the variation of the pixel points in the time direction is larger than a second threshold;

comparing the obtained ratio value with a fourth threshold value;

if the obtained ratio is larger than the fourth threshold, determining that the interlace type of the video image to be detected is the interlace type;

and if the obtained ratio is not larger than the fourth threshold, determining that the interlaced type of the video image to be detected is the progressive type.

4. The method of claim 1, wherein said calculating the sum of absolute values of differences of pixel points at corresponding locations in two of said four images comprises:

dividing the four frame images into two pairs of images;

and calculating the sum of the absolute values of the differences of the pixel points at the corresponding positions in each pair of images.

5. The method of claim 4, wherein a first pair of images of the two pairs of images comprises: the bottom field formed by dividing the previous frame of video image to be detected in the two adjacent frames of video images to be detected and the top field formed by filling are spliced to form an image, and the top field formed by dividing the next frame of video image to be detected in the two adjacent frames of video images to be detected and the bottom field formed by filling are spliced to form an image; a second pair of images of the two pairs of images comprising: the top field formed by dividing the previous frame of video image to be detected in the two adjacent frames of video images to be detected and the bottom field formed by filling are spliced to form an image, and the bottom field formed by dividing the next frame of video image to be detected in the two adjacent frames of video images to be detected and the top field formed by filling are spliced to form an image.

6. The method according to claim 5, wherein the analyzing the sum of absolute values of differences between pixel points at corresponding positions in two of the four frames of images to determine the field priority of the video to be detected comprises:

comparing the sum of the absolute values of the differences of the pixel points at the corresponding positions in the first pair of images with the sum of the absolute values of the differences of the pixel points at the corresponding positions in the second pair of images;

if the sum of the absolute values of the differences of the pixel points at the corresponding positions in the first pair of images is larger than the sum of the absolute values of the differences of the pixel points at the corresponding positions in the second pair of images, determining that the field priority order of the video to be detected is bottom field priority;

and if the sum of the absolute values of the differences of the pixel points at the corresponding positions in the first pair of images is not more than the sum of the absolute values of the differences of the pixel points at the corresponding positions in the second pair of images, determining that the field priority order of the video to be detected is top field priority.

7. The method of claim 1, wherein the method further comprises:

and generating a detection result of the video to be detected in response to the fact that the interlace type of the video to be detected is determined to be a progressive type, wherein the detection result of the video to be detected comprises the interlace type of the video to be detected.

8. The method according to one of claims 1 to 7, wherein the method further comprises:

and outputting the detection result of the video to be detected.

9. An electronic device, comprising:

one or more processors;

storage means for storing one or more programs;

when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-8.

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

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