WO2021035687A1

WO2021035687A1 - Open-field experiment data analysis method and system and terminal device

Info

Publication number: WO2021035687A1
Application number: PCT/CN2019/103707
Authority: WO
Inventors: 陈高伟; 朱英杰; 周魁魁; 姜少磊
Original assignee: 深圳先进技术研究院
Priority date: 2019-08-30
Filing date: 2019-08-30
Publication date: 2021-03-04

Abstract

An open-field experiment data analysis method, comprising: obtaining an experiment video comprising a target open field, and extracting each video frame corresponding to the experiment video; converting each video frame into a corresponding binary image, and capturing a region image corresponding to the target open field from each binary image; obtaining a first coordinate corresponding to each pixel of an experimental animal in each region image, and determining a second coordinate corresponding to the centroid of the experimental animal in each region image according to the first coordinate corresponding to each pixel; and establishing a coordinate system according to the contour boundary of the target open field in the region image, and drawing a motion trajectory of the experimental animal in the coordinate system according to the second coordinate corresponding to each centroid, so as to reduce the time cost in open-field experimental data analysis and improve the analysis efficiency and accuracy of open-field experimental data analysis. Also provided are a system and a terminal device.

Description

An open field experiment data analysis method, system and terminal equipment

Technical field

This application belongs to the field of data processing technology, and in particular relates to an open field experiment data analysis method, system and terminal equipment.

Background technique

In the current animal behavior experiment-open field experiment data analysis method, it is usually to record the animal behavior in the open field first, then play the recorded video, and manually observe and analyze the played video to obtain the animal The behavioral data not only consumes a lot of time and cost, but also the efficiency and accuracy of data analysis is low.

technical problem

The embodiments of the present application provide an open field experimental data analysis method, system and terminal equipment, which can solve the problem of low efficiency and accuracy of open field experimental data analysis in the prior art.

Technical solutions

In the first aspect, an embodiment of the present application provides an open field experiment data analysis method, including:

Acquiring an experimental video containing the target open field, and extracting each video frame corresponding to the experimental video;

Converting each of the video frames into a corresponding binary image, and intercepting an area image corresponding to the target open field from each of the binary images;

Acquiring the first coordinates corresponding to each pixel of the experimental animal in each of the regional images, and determining the second coordinate corresponding to the centroid of the experimental animal in each of the regional images according to the first coordinate corresponding to each of the pixel;

A coordinate system is established according to the contour boundary of the target open field in the regional image, and the motion track of the experimental animal is drawn in the coordinate system according to the second coordinates corresponding to each of the centroids.

In a possible implementation manner of the first aspect, the converting each of the video frames into corresponding binary images includes:

Converting each of the video frames into corresponding gray-scale images;

Acquiring an initial segmentation threshold, and converting each of the grayscale images into a corresponding initial binary image according to the initial segmentation threshold;

Determining whether the initial binary image meets a preset condition;

If the initial binary image satisfies the preset condition, determining each initial binary image as a binary image corresponding to each video frame;

If the initial binary image does not meet the preset condition, adjust the initial segmentation threshold, and return to execute the step of converting each of the grayscale images into the corresponding initial binary image according to the initial segmentation threshold; and Next steps.

Optionally, the intercepting the region image corresponding to the target open field from each of the binary images includes:

Displaying any one of the grayscale images to instruct the user to set the contour boundary corresponding to the target open field according to the displayed grayscale image;

The region image corresponding to the open field of the target is intercepted from each of the binary images according to the contour boundary.

In a possible implementation of the first aspect, after determining the second coordinate corresponding to the centroid of the experimental animal in each of the regional images according to the first coordinate corresponding to each pixel point, the method includes:

Determining the moving distance of the experimental animal according to the second coordinates corresponding to each of the centroids;

Obtain the video duration of the experimental video, and determine the moving speed of the experimental animal according to the moving distance and the video duration.

Optionally, the determining the moving distance of the experimental animal according to the second coordinates corresponding to each of the centroids includes:

Respectively calculating the centroid distance between the centroids of the experimental animals in two adjacent frames of regional images according to the second coordinates corresponding to the centroids;

The moving distance of the experimental animal is determined based on each of the centroid distances.

Specifically, the establishing a coordinate system according to the contour boundary of the target open field in the area image includes:

The coordinate system is established by taking the left contour boundary of the target open field in the area image as the vertical axis, and taking the lower contour boundary of the target open field as the horizontal axis.

In a possible implementation manner of the first aspect, after establishing a coordinate system according to the contour boundary of the target open field in the area image, the method includes:

Determining a target area in the coordinate system, and determining a first number of centroids located in the target area according to the second coordinates corresponding to each of the centroids and the coordinate range corresponding to the target area;

Determining a second number of the centroids, where the second number is the total number of centroids included in the motion track;

Obtain the video duration of the experimental video;

The activity time of the experimental animal in the target area is determined according to the video duration, the first quantity and the second quantity.

Optionally, the acquiring the experimental video including the target open field includes:

Obtain the video path and video name corresponding to the experimental video containing the target open field;

Obtain the experimental video containing the target mine according to the video path and the video name.

In the second aspect, an embodiment of the present application provides an open field experiment data analysis system, including:

The video frame extraction module is used to obtain the experimental video containing the target open field, and extract each video frame corresponding to the experimental video;

An area image interception module, configured to convert each of the video frames into a corresponding binary image, and intercept the area image corresponding to the target open field from each of the binary images;

The centroid coordinate determination module is used to obtain the first coordinate corresponding to each pixel of the experimental animal in each of the regional images, and determine the first coordinate of the experimental animal in each of the regional images according to the first coordinate corresponding to each pixel. The second coordinate corresponding to the centroid;

The motion trajectory drawing module is used to establish a coordinate system according to the outline boundary of the target open field in the regional image, and draw the motion trajectory of the experimental animal in the coordinate system according to the second coordinates corresponding to each of the centroids .

In a third aspect, an embodiment of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, The open field experiment data analysis method as described in any one of the above-mentioned first aspects is realized.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the implementation is as described in any of the above-mentioned first aspects. The open field experiment data analysis method described.

In a fifth aspect, the embodiments of the present application provide a computer program product that, when the computer program product runs on a terminal device, causes the terminal device to execute the open-field experiment data analysis method described in any one of the above-mentioned first aspects.

Beneficial effect

In the embodiment of this application, after acquiring the experimental video containing the target open field, the video frame of the experimental video can be extracted directly without video playback, and the extracted video frames can be binarized After processing, the binary image corresponding to each video frame is obtained, and then the regional image corresponding to the target open field can be intercepted from each binary image, and the coordinate system corresponding to the target open field can be established by analyzing the regional image and the experimental animal The coordinates corresponding to the centroids in the images of each area can be quickly and accurately drawn in the coordinate system according to the coordinates corresponding to the centroids, which greatly reduces the time cost in the open field experimental data analysis and effectively improves The analysis efficiency and accuracy of open field experiment data analysis are improved.

Description of the drawings

FIG. 1 is a schematic flowchart of an open field experiment data analysis method provided by an embodiment of the present application;

2 is a schematic flowchart of a binary image obtained in an application scenario by the open field experimental data analysis method provided by an embodiment of the present application;

FIG. 3 is a schematic diagram of a grayscale image obtained in an application scenario according to an embodiment of the present application;

FIG. 4 is a schematic diagram of contour boundaries set in an application scenario according to an embodiment of the present application;

FIG. 5 is a schematic diagram of a motion trajectory diagram obtained in an application scenario according to an embodiment of the present application;

FIG. 6 is a schematic flow chart of determining the activity time of an experimental animal in a target area in an application scenario according to an open field experimental data analysis method provided by an embodiment of the present application;

FIG. 7 is a schematic structural diagram of an open field experiment data analysis system provided by an embodiment of the present application;

Fig. 8 is a schematic structural diagram of a terminal device provided by an embodiment of the present application.

Embodiments of the present invention

In the following description, for the purpose of illustration rather than limitation, specific details such as a specific system structure and technology are proposed for a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from obstructing the description of this application.

It should be understood that when used in the specification and appended claims of this application, the term "comprising" indicates the existence of the described features, wholes, steps, operations, elements and/or components, but does not exclude one or more other The existence or addition of features, wholes, steps, operations, elements, components, and/or collections thereof.

It should also be understood that the term "and/or" used in the specification and appended claims of this application refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

As used in the description of this application and the appended claims, the term "if" can be construed as "when" or "once" or "in response to determination" or "in response to detecting ". Similarly, the phrase "if determined" or "if detected [described condition or event]" can be interpreted as meaning "once determined" or "in response to determination" or "once detected [described condition or event]" depending on the context ]" or "in response to detection of [condition or event described]".

In addition, in the description of the specification of this application and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

Reference to "one embodiment" or "some embodiments" described in the specification of this application means that one or more embodiments of this application include a specific feature, structure, or characteristic described in combination with the embodiment. Therefore, the sentences "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. appearing in different places in this specification are not necessarily All refer to the same embodiment, but mean "one or more but not all embodiments" unless it is specifically emphasized otherwise. The terms "including", "including", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

An open field experiment refers to an experiment in which animals are placed in an open field experimental device and their activities in the open field experimental device are recorded to analyze and obtain animal behavior data. The existing open-field experimental data analysis methods generally need to play the recorded video to obtain animal behavior data by manual observation and analysis during the playback process, which not only takes a lot of time for the experimenter, but also easily reduces the amount of open-field experimental data analysis. Analysis efficiency and analysis accuracy.

In order to solve the above problems, the embodiments of the present application provide an open field experiment data analysis method, system, and terminal equipment, which can directly extract video frames from the experimental video in the open field experiment without video playback. The extracted video frames can be binarized to obtain the binary image corresponding to each video frame, and then the regional image corresponding to the target open field can be intercepted from each binary image, and the regional image can be analyzed Establish the coordinate system corresponding to the target open field (that is, the area corresponding to the open field experimental device in the image) and the coordinate corresponding to the centroid of the experimental animal in the image of each area, so that the coordinate corresponding to each centroid can be quickly and quickly in the coordinate system. Accurately draw the motion trajectory of experimental animals.

Optionally, the open-field experimental data analysis method in the embodiments of the present application can be applied to scenarios where there is a color difference between the open-field experimental device and the experimental animal, for example, it can be applied to the open-field experimental device being white and the experimental animal being black. In the scene, or can be applied to the scene where the open field experimental device is black, the experimental animal is white, and so on. The open field experimental data analysis method provided in the embodiments of the present application will be described in detail below with a scene where the open field experimental device is white and the experimental animal is black.

FIG. 1 shows a schematic flowchart of an open field experimental data analysis method provided by an embodiment of the present application, and the open field experimental data analysis method may include:

Step S101: Obtain an experimental video containing the target open field, and extract each video frame corresponding to the experimental video;

The execution subject of the embodiments of the application may be an open field experimental data analysis system based on the Matlab language. The open field experimental analysis system is constructed using the open source Matlab language, which can ensure the convenience and lightness of the constructed system and make all The construction system can be used simply and quickly, reducing the experimental cost of open field experiments. The open field experiment data analysis system can be installed in any terminal device to run and use, and the terminal device includes, but is not limited to, computing devices such as desktop computers, notebooks, and palm computers. Wherein, the experimental video can be recorded video in various formats, for example, can be recorded video in wmv (Windows Media Video) format, or can be recorded video in rmvb (Real Media Variable Bitrate) format, or can be mkv (Matroska Video) format recording video, or it can be avi (Audio Video Interleaved) format recording video, etc.

It should be understood that after the video recording of an open field experiment is completed for a certain target open field, the recorded experimental video containing the target open field can be stored in the storage device of the terminal device or stored in the storage device connected to the terminal device. In the cloud server. Here, the experimental video including the open field of the target refers to the video that is recorded when the open field of the target can be completely captured. When data analysis of the open field experiment is required, the experimental video containing the target open field may be obtained from the storage device or from the cloud server. Specifically, when an open field experimental data analysis is required, the user can input the video path and video name corresponding to the experimental video containing the target open field into the open field experimental data analysis system, and the open field experimental data analysis The system can obtain the experimental video by interpreting the video path and the video name. For example, the open field experiment data analysis system may interpret the video path and the video name to obtain the experiment video in the following manner:

datapath = 'C:\Users\pinbo\Desktop\matlab_test\open_field_ana';

datafile = 'CON_1.wmv';

cd(datapath);

tit_fn = sprintf('%s',datafile(1:end-4));

It should be understood that after the open field experimental data analysis system obtains the experimental video, the reading function (such as video = VideoReader (datafile)) to read the experimental video, and can extract the video frames corresponding to the experimental video in real time during the video reading process. For example, the video frames corresponding to the experimental video can be extracted in sequence according to the video sequence. Wherein, when the open-field experimental data analysis system reads the experimental video, it can also obtain the video duration and frame rate of the experimental video, and can determine the extracted data according to the video duration and the frame rate. The number of video frames, for example, the number of extracted video frames can be determined according to the number of frames = video duration * frame rate, that is, the open field experimental data analysis system can extract the number of frames during the video reading process Video frames.

Step S102: Convert each of the video frames into a corresponding binary image, and intercept an area image corresponding to the target open field from each of the binary images;

Specifically, as shown in FIG. 2, the converting each of the video frames into corresponding binary images may include:

Step S201: Convert each of the video frames into corresponding gray-scale images;

In the embodiment of the present application, each of the frequency frames may be first converted into a grayscale image with a grayscale range of 0 to 1, that is, the grayscale value of each pixel in each grayscale image is 0. In this case, any existing gray-scale conversion method may be used to convert each of the video frames into corresponding gray-scale images, which is not limited in the embodiment of the present application.

Step S202: Obtain an initial segmentation threshold, and convert each of the grayscale images into corresponding initial binary images according to the initial segmentation threshold;

It should be noted that the initial segmentation threshold can be determined through experimental tests, and the range of the initial segmentation threshold is between 0 and 1. For example, the initial segmentation threshold can be set to 0.3 according to experimental tests. Here, after the initial segmentation threshold is obtained, for each frame of grayscale image, the grayscale value of each pixel in the grayscale image can be obtained first, and then the grayscale value can be greater than the initial segmentation threshold. The gray value of the pixel is reset to 1 (that is, the pixel value of the pixel corresponding to the experimental animal is set to 1), and the gray value of the pixel whose gray value is less than or equal to the initial segmentation threshold can be reset Set it to 0 (that is, set the pixel value of the pixel corresponding to the open field experimental device to 0), so as to obtain the initial binary image with the pixel gray value of 0 or 1. For example, in a scene where the initial segmentation threshold is 0.3, the gray values of pixels with gray values greater than 0.3 can be set to 1, and the gray values of pixels with gray values less than or equal to 0.3 can be set to average. Set to 0.

Step S203: Determine whether the initial binary image meets a preset condition;

Step S204: If the initial binary image satisfies the preset condition, determine each initial binary image as a binary image corresponding to each video frame;

Step S205: If the initial binarized image does not meet the preset condition, adjust the initial segmentation threshold, and return to execute converting each grayscale image into a corresponding initial binary image according to the initial segmentation threshold Steps and subsequent steps.

For the above steps S203 to S205, the open field experimental data analysis system can display the initial binary image on the display interface after obtaining the initial binary image of any grayscale image according to the initial segmentation threshold. Instruct the user to determine whether the displayed initial binary image satisfies a preset condition, that is, instruct the user to determine whether the experimental animal in the initial binary image and the target open field are segmented correctly, and feed back corresponding response information, such as Feed back the correct response information between the experimental animal and the target open field, or feedback the incorrect response information between the experimental animal and the target open field. The open field experimental data analysis system may determine whether the initial binary image satisfies a preset condition according to the response information, and if it is determined that the initial binary image satisfies the preset condition, each of the initial binary images may be The binary image is determined to be the binary image corresponding to each of the video frames; if it is determined that the initial binary image does not meet the preset condition, the initial segmentation threshold may be adjusted. Here, in the response information When segmenting incorrect response information between the experimental animal and the target open field, the response information can also carry the adjusted segmentation threshold input by the user, and the open field experimental data analysis system can be based on the The initial segmentation threshold is adjusted by the segmentation threshold carried in the response information, and the initial segmentation threshold can be adjusted to the segmentation threshold carried in the response information, and the grayscale can be continuously executed according to the initial segmentation threshold. The step of converting the degree image into the corresponding initial binary image and subsequent steps until it is determined that the initial binary image satisfies the preset condition.

It should be noted that the adjustment of the initial segmentation threshold according to the segmentation threshold input by the user is only for schematic explanation, and should not be construed as a limitation of the embodiment of the present application. Of course, the embodiment of the present application can also automatically perform the initial segmentation threshold according to image recognition technology. Adjustment.

It should be understood that the open field experimental device corresponding to the target open field is always at a fixed position during the video recording process, so that the target open field has the same area in all video frames, that is, the target open field is in all two areas. The areas in the value image are also the same. Therefore, in a possible implementation, the open-field experimental data analysis system can display any gray-scale image on the display interface after obtaining the gray-scale image corresponding to each video frame (as shown in Figure 3). To instruct the user to set the contour boundary corresponding to the target open field according to the displayed gray image (for example, the gray image shown in Fig. 3 can be the rectangular in the open field experimental device). The frame is set as the contour boundary corresponding to the target open field as shown in Fig. 4), the open field experimental data analysis system can receive the contour boundary set by the user, and can use the contour boundary from each of the binary values The area image corresponding to the open field of the target is intercepted in the image to perform subsequent data analysis by intercepting the image of the area corresponding to the open field of the target, which can greatly reduce the analysis workload in the data analysis, thereby improving the data analysis of the open field experiment Analysis efficiency.

It should be noted that the outline boundary of the target open field set by the user is only for schematic explanation, and should not be construed as a limitation to the embodiment of the present application. Of course, the embodiment of the present application can also automatically determine the corresponding target open field based on image recognition technology. Contour boundary.

In a possible implementation manner, it is also possible to perform the interception operation of the area image first, and then perform the conversion operation of the binary image, that is, the area image corresponding to the target open field may be intercepted first from each video frame, and then The binarization conversion process can be performed on each region image, and the centroid of the region image after the binarization conversion process can be determined later, so that the region image can be intercepted first and then the region image binarization process. Reduce the processing workload in the binarization process, thereby improving the analysis efficiency of open field experimental data analysis.

Step S103: Obtain the first coordinates corresponding to each pixel of the experimental animal in each of the regional images, and determine the first coordinate corresponding to the centroid of the experimental animal in each of the regional images according to the first coordinate corresponding to each pixel. Two coordinates

Here, the open field experimental data analysis system can obtain the first coordinates corresponding to each pixel of the experimental animal in each of the regional images after intercepting the images of each area corresponding to the target open field, that is, obtain each The first coordinate corresponding to the pixel with the gray value of 1 in the regional image, and the centroid of the experimental animal in each regional image can be determined according to the first coordinate corresponding to each pixel in each regional image The corresponding second coordinate, for example, the second coordinate corresponding to the centroid A of the experimental animal in the first frame of regional image can be calculated according to the first coordinate corresponding to the pixel with the gray value of 1 in the first frame of regional image, The second coordinate corresponding to the centroid B of the experimental animal in the second frame area image is calculated according to the first coordinate corresponding to the pixel with the gray value of 1 in the second frame area image, and so on, until according to the last frame The first coordinate corresponding to the pixel with the gray value of 1 in the area image is calculated until the second coordinate corresponding to the centroid of the experimental animal in the last frame of the area image is obtained. Specifically, the open field experimental data analysis system may calculate the second coordinate coordinate.cdata corresponding to the centroid of the experimental animal in each of the regional images by calling the following method:

BW3 = double(BW_adjust);

[rows,cols] = size(BW3);

x = ones(rows,1)*(1:cols);

y = (1:rows)'*ones(1,cols);

area = sum(sum(BW3));

meanx = sum(sum(BW3.*x))/area;

meany = sum(sum(BW3.*y))/area;

coordinate.cdata{i,1} = [meanx,meany];

End

In a possible implementation manner, after determining the second coordinate corresponding to the centroid of the experimental animal in each of the regional images according to the first coordinate corresponding to each pixel point, the method may further include:

Step a: Determine the moving distance of the experimental animal according to the second coordinates corresponding to each of the centroids;

Specifically, the determining the moving distance of the experimental animal according to the second coordinates corresponding to each of the centroids may include: step a1, respectively, calculating all the images in the two adjacent frames of area images according to the second coordinates corresponding to each of the centroids. The centroid distance between the centroids of the experimental animals; step a2, the moving distance of the experimental animals is determined based on each of the centroid distances.

It should be understood that the final moving distance of the experimental animal can be determined according to the centroid distance between the centroids of the experimental animal in two consecutive frames of regional images, that is, the centroid distance of the experimental animal in every two consecutive frames of regional images can be calculated first , And then the centroid distances can be added together to obtain the final moving distance of the experimental animal.

Step b: Obtain the video duration of the experimental video, and determine the moving speed of the experimental animal according to the moving distance and the video duration.

In this embodiment of the application, when the open field experimental data analysis system reads the experimental video, it can also acquire the video duration of the experimental video. Therefore, after determining the final moving distance of the experimental animal, it can be based on The movement distance and the video duration determine the movement rate of the experimental animal. For example, the movement distance/video duration may be used to obtain the movement rate.

Step S104: Establish a coordinate system according to the outline boundary of the target open field in the area image, and draw the motion track of the experimental animal in the coordinate system according to the second coordinates corresponding to each of the centroids;

Specifically, the establishing a coordinate system according to the contour boundary of the target open field in the regional image may include: taking the left contour boundary of the target open field in the regional image as the vertical axis, and taking the target open field as the vertical axis. The lower contour boundary of is the horizontal axis to establish the coordinate system.

Here, after the coordinate system is established, the motion trajectory of the experimental animal can be drawn in the coordinate system according to the second coordinates corresponding to each centroid, that is, the centroid is used to characterize the experimental animal's movement at the target. The position in the open field, so as to reflect the movement of the experimental animal in the target open field according to the coordinate change of the center of mass. Specifically, the centroids in two consecutive frames of regional images may be connected to obtain the motion trajectory of the experimental animal in the open field of the target. In the embodiment of the present application, after the motion trajectory is obtained, the contour boundary of the motion trajectory can also be drawn according to the contour boundary of the target open field. For example, in a specific application scenario, the target open field can be drawn The contour boundary of is drawn as the contour boundary of the motion trajectory, so that the motion trajectory diagram shown in FIG. 5 is obtained.

It should be understood that after obtaining the motion trajectory diagram of the experimental animal, a save path can be set to save the motion path diagram, so as to facilitate subsequent viewing and analysis of open field experimental data.

In another possible implementation manner, as shown in FIG. 6, after establishing a coordinate system according to the contour boundary of the target open field, it may include:

Step S601: Determine a target area in the coordinate system, and determine a first number of centroids located in the target area according to the second coordinates corresponding to each of the centroids and the coordinate range corresponding to the target area;

Step S602: Determine a second number of the centroids, where the second number is the total number of the centroids included in the motion trajectory;

Step S603: Obtain the video duration of the experimental video;

Step S604: Determine the activity time of the experimental animal in the target area according to the video duration, the first quantity and the second quantity.

For the above steps S601 to S604, in an open field experiment, it is often necessary to analyze the residence time of the experimental animal in a specific target area, etc. In the embodiment of the present application, after the coordinate system corresponding to the target open field is established, the user can also be instructed to set the coordinate range of the target area in the coordinate system, and the open field experimental data analysis system can be based on The coordinate range set by the user determines the target area in the coordinate system, for example, the target area as shown in FIG. 5 (that is, the small rectangular area in the motion trajectory diagram in FIG. 5) is determined.

After the target area is determined, the open field experimental data analysis system can first determine the second coordinate of the center of mass located in the target area according to the second coordinate corresponding to each of the center of mass and the coordinate range corresponding to the target area. A number, and a second number of the centroids can be obtained. The second number is the total number of the centroids in the experimental video. Here, the total number of the centroids can be determined according to the drawn motion trajectory. In addition, because each video frame in the experimental video can include the experimental animal, in the embodiment of this application, of course, the experimental video can also be determined according to the number of video frames corresponding to the experimental video. According to the total number of centroids, the number of frames of the video frame can be determined as the total number of centroids; then the video duration of the experimental video can be obtained, and the video duration can be determined according to the video duration, the first number and The second number determines the activity time of the experimental animal in the target area, for example, it can be determined that the experimental animal is in the target area according to activity time = video duration * (first number/second number) In order to quickly and accurately obtain the behavior data of the experimental animals in the specific target area in the open field experiment.

In the embodiment of this application, firstly, the experimental video containing the target open field is obtained, and each video frame corresponding to the experimental video is directly extracted; then, each of the video frames is converted into a corresponding binary image, and each of the two The area image corresponding to the target open field is intercepted from the value image; then the first coordinates corresponding to each pixel of the experimental animal in each of the area images are obtained, and each of the pixels is determined according to the first coordinates corresponding to the pixels. The second coordinate corresponding to the centroid of the experimental animal in the regional image; finally a coordinate system is established according to the contour boundary of the target open field in the regional image, and the second coordinate corresponding to each centroid is in the coordinate system Draw the motion trajectory of the experimental animal in. That is, in the embodiment of the present application, after the experimental video is obtained, the video frame of the experimental video can be extracted directly without video playback, and the extracted video frames can be binarized to obtain each The binary image corresponding to the video frame can be intercepted from each binary image and the area image corresponding to the open field of the target can be intercepted, and the coordinate system corresponding to the open field of the target can be established by analyzing the regional image and the experimental animal in each area image The coordinates corresponding to the center of mass of each center of mass can quickly and accurately draw the motion trajectory of the experimental animal in the coordinate system according to the coordinate corresponding to each center of mass, which greatly reduces the time cost in the data analysis of the open field experiment, and effectively improves the open field experiment Analysis efficiency and accuracy of data analysis.

It should be understood that the size of the sequence number of each step in the foregoing embodiment does not mean the order of execution. The execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

Corresponding to the open field experimental data analysis method described in the above embodiment, FIG. 7 shows a structural block diagram of the open field experimental data analysis system provided in an embodiment of the present application. The relevant part.

Referring to Figure 7, the open field experiment data analysis system includes:

The video frame extraction module 701 is configured to obtain an experimental video containing a target open field, and extract each video frame corresponding to the experimental video;

An area image interception module 702, configured to convert each of the video frames into a corresponding binary image, and intercept the area image corresponding to the target open field from each of the binary images;

The centroid coordinate determination module 703 is used to obtain the first coordinates corresponding to each pixel of the experimental animal in each of the regional images, and determine the experimental animal in each of the regional images according to the first coordinates corresponding to each of the pixel points The second coordinate corresponding to the centroid of;

The motion trajectory drawing module 704 is configured to establish a coordinate system according to the outline boundary of the target open field in the area image, and draw the motion of the experimental animal in the coordinate system according to the second coordinates corresponding to each of the centroids Trajectory.

In a possible implementation manner, the regional image capturing module 702 may include:

An area image conversion unit for converting each of the area images into corresponding grayscale images;

A segmentation threshold acquisition unit, configured to acquire an initial segmentation threshold, and convert each of the grayscale images into a corresponding initial binary image according to the initial segmentation threshold;

A binary image judging unit, configured to determine whether the initial binary image satisfies a preset condition;

A binary image determining unit, configured to determine each initial binary image as a binary image corresponding to each video frame if the initial binary image satisfies the preset condition;

The segmentation threshold adjustment unit is configured to adjust the initial segmentation threshold if the initial binarized image does not meet the preset condition, and return to execute converting each of the grayscale images into corresponding ones according to the initial segmentation threshold The initial binary image steps and subsequent steps.

Optionally, the regional image capturing module 702 may further include:

A grayscale image display unit for displaying any one of the grayscale images to instruct the user to set the contour boundary corresponding to the target open field according to the displayed grayscale image;

The area image interception unit is configured to intercept the area image corresponding to the target open field from each of the binary images according to the contour boundary.

In a possible implementation manner, the open field experiment data analysis system may further include:

A moving distance determining module, configured to determine the moving distance of the experimental animal according to the second coordinates corresponding to each of the centroids;

The moving rate determining module is used to obtain the video duration of the experimental video, and determine the moving rate of the experimental animal according to the moving distance and the video duration.

Optionally, the moving distance determining module may include:

A centroid distance calculation unit, configured to calculate the centroid distance between the centroids of the experimental animals in two adjacent frames of regional images according to the second coordinates corresponding to each centroid;

The moving distance determining unit is configured to determine the moving distance of the experimental animal based on each of the centroid distances.

Specifically, the motion trajectory drawing module 704 is specifically configured to use the left contour boundary of the target open field in the area image as the vertical axis, and the lower contour boundary of the target open field as the horizontal axis to establish the coordinates system.

Optionally, the open field experiment data analysis system may further include:

The target area determination module is configured to determine a target area in the coordinate system, and determine the first number of centroids located in the target area according to the second coordinates corresponding to each of the centroids and the coordinate range corresponding to the target area ；

A centroid quantity determination module, configured to determine a second quantity of the centroid, where the second quantity is the total quantity of centroids included in the motion trajectory;

The video duration acquisition module is used to acquire the video duration of the experimental video;

The activity time determination module is configured to determine the activity time of the experimental animal in the target area according to the video duration, the first quantity and the second quantity.

Optionally, the video frame extraction module 701 may include:

The path name obtaining unit is used to obtain the video path and video name corresponding to the experimental video containing the target open field;

The experimental video acquisition unit is configured to acquire the experimental video containing the target mine according to the video path and the video name.

It should be noted that the information interaction and execution process between the above-mentioned devices/units are based on the same concept as the method embodiment of this application, and its specific functions and technical effects can be found in the method embodiment section. I won't repeat it here.

Those skilled in the art can clearly understand that for the convenience and conciseness of description, only the division of the above functional units and modules is used as an example. In practical applications, the above functions can be allocated to different functional units and modules as required. Module completion, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated in one processing unit, or each unit can exist alone physically, or two or more units can be integrated in one unit. The above-mentioned integrated units can be hardware-based Formal realization can also be realized in the form of software functional units. In addition, the specific names of the functional units and modules are only used to facilitate distinguishing each other, and are not used to limit the protection scope of the present application. For the specific working process of the units and modules in the foregoing system, reference may be made to the corresponding process in the foregoing method embodiment, which will not be repeated here.

FIG. 8 is a schematic structural diagram of a terminal device provided by an embodiment of this application. As shown in FIG. 8, the terminal device 8 of this embodiment includes: at least one processor 80 (only one is shown in FIG. 8), a processor, a memory 81, and a processor that is stored in the memory 81 and can be processed in the at least one processor. A computer program 82 running on the processor 80, when the processor 80 executes the computer program 82, the steps in any of the above-mentioned open field experimental data analysis method embodiments are implemented.

The terminal device 8 may be a computing device such as a desktop computer, a notebook, a palmtop computer, and a cloud server. The terminal device may include, but is not limited to, a processor 80 and a memory 81. Those skilled in the art can understand that FIG. 8 is only an example of the terminal device 8 and does not constitute a limitation on the terminal device 8. It may include more or less components than those shown in the figure, or a combination of certain components, or different components. , For example, can also include input and output devices, network access devices, and so on.

The so-called processor 80 may be a central processing unit (Central Processing Unit, CPU), the processor 80 may also be other general-purpose processors or digital signal processors (Digital Signal Processor, DSP), Application Specific Integrated Circuit (ASIC), ready-made programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like.

The memory 81 may be an internal storage unit of the terminal device 8 in some embodiments, such as a hard disk or memory of the terminal device 8. In other embodiments, the memory 81 may also be an external storage device of the terminal device 8, such as a plug-in hard disk equipped on the terminal device 8, a smart memory card (Smart Media Card, SMC), and a secure digital (Secure Digital, SD) card, flash memory card (Flash Card) and so on. Further, the memory 81 may also include both an internal storage unit of the terminal device 8 and an external storage device. The memory 81 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 81 can also be used to temporarily store data that has been output or will be output.

The embodiments of the present application also provide a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in each of the foregoing method embodiments can be realized.

The embodiments of the present application provide a computer program product. When the computer program product runs on a terminal device, the terminal device can realize the steps in the foregoing method embodiments when executed.

If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the implementation of all or part of the processes in the above-mentioned embodiment methods in this application can be accomplished by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When executed by the processor, the steps of the foregoing method embodiments can be implemented. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file, or some intermediate forms. The computer-readable medium may at least include: any entity or device capable of carrying the computer program code to the photographing device/terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signals, telecommunications signals, and software distribution media. For example, U disk, mobile hard disk, floppy disk or CD-ROM, etc. In some jurisdictions, according to legislation and patent practices, computer-readable media cannot be electrical carrier signals and telecommunication signals.

In the above-mentioned embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail or recorded in an embodiment, reference may be made to related descriptions of other embodiments.

A person of ordinary skill in the art may realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software depends on the specific application and design constraint conditions of the technical solution. Professionals and technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered beyond the scope of this application.

In the embodiments provided in this application, it should be understood that the disclosed apparatus/equipment and method may be implemented in other ways. For example, the device/equipment embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or Components can be combined or integrated into another system, or some features can be omitted or not implemented. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.

The above-mentioned embodiments are only used to illustrate the technical solutions of the present application, not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, a person of ordinary skill in the art should understand that it can still implement the foregoing The technical solutions recorded in the examples are modified, or some of the technical features are equivalently replaced; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the application, and should be included in Within the scope of protection of this application.

Claims

An open field experimental data analysis method, which is characterized in that it comprises:

Acquiring an experimental video containing the target open field, and extracting each video frame corresponding to the experimental video;

Converting each of the video frames into a corresponding binary image, and intercepting an area image corresponding to the target open field from each of the binary images;

Acquiring the first coordinates corresponding to each pixel of the experimental animal in each of the regional images, and determining the second coordinate corresponding to the centroid of the experimental animal in each of the regional images according to the first coordinate corresponding to each of the pixel;

A coordinate system is established according to the contour boundary of the target open field in the regional image, and the motion track of the experimental animal is drawn in the coordinate system according to the second coordinates corresponding to each of the centroids.
The open-field experimental data analysis method according to claim 1, wherein said converting each of said video frames into corresponding binary images comprises:

Converting each of the video frames into corresponding gray-scale images;

Acquiring an initial segmentation threshold, and converting each of the grayscale images into a corresponding initial binary image according to the initial segmentation threshold;

Determining whether the initial binary image meets a preset condition;

If the initial binary image satisfies the preset condition, determining each initial binary image as a binary image corresponding to each video frame;

If the initial binary image does not meet the preset condition, adjust the initial segmentation threshold, and return to execute the step of converting each of the grayscale images into the corresponding initial binary image according to the initial segmentation threshold; and Next steps.
3. The open field experimental data analysis method according to claim 2, wherein the intercepting the region image corresponding to the target open field from each of the binary images comprises:

Displaying any one of the grayscale images to instruct the user to set the contour boundary corresponding to the target open field according to the displayed grayscale image;

The region image corresponding to the open field of the target is intercepted from each of the binary images according to the contour boundary.
The open-field experimental data analysis method of claim 1, wherein after determining the second coordinate corresponding to the centroid of the experimental animal in each of the regional images according to the first coordinate corresponding to each pixel point, include:

Determining the moving distance of the experimental animal according to the second coordinates corresponding to each of the centroids;

Obtain the video duration of the experimental video, and determine the moving speed of the experimental animal according to the moving distance and the video duration.
The open field experimental data analysis method of claim 4, wherein the determining the moving distance of the experimental animal according to the second coordinate corresponding to each of the centroids comprises:

Respectively calculating the centroid distance between the centroids of the experimental animals in two adjacent frames of regional images according to the second coordinates corresponding to the centroids;

The moving distance of the experimental animal is determined based on each of the centroid distances.
The open field experimental data analysis method according to claim 1, wherein the establishing a coordinate system according to the outline boundary of the target open field in the regional image comprises:

The coordinate system is established by taking the left contour boundary of the target open field in the area image as the vertical axis, and taking the lower contour boundary of the target open field as the horizontal axis.
The open field experimental data analysis method according to claim 1, wherein after establishing a coordinate system according to the outline boundary of the target open field in the area image, the method comprises:

Determining a target area in the coordinate system, and determining a first number of centroids located in the target area according to the second coordinates corresponding to each of the centroids and the coordinate range corresponding to the target area;

Determining a second number of the centroids, where the second number is the total number of centroids included in the motion track;

Obtain the video duration of the experimental video;

The activity time of the experimental animal in the target area is determined according to the video duration, the first quantity and the second quantity.
The method for analyzing open field experimental data according to any one of claims 1 to 7, wherein said acquiring an experimental video containing a target open field comprises:

Obtain the video path and video name corresponding to the experimental video containing the target open field;

Obtain the experimental video containing the target mine according to the video path and the video name.
An open field experiment data analysis system, which is characterized in that it comprises:

The video frame extraction module is used to obtain the experimental video containing the target open field, and extract each video frame corresponding to the experimental video;

An area image interception module, configured to convert each of the video frames into a corresponding binary image, and intercept the area image corresponding to the target open field from each of the binary images;

The centroid coordinate determination module is used to obtain the first coordinate corresponding to each pixel of the experimental animal in each of the regional images, and determine the first coordinate of the experimental animal in each of the regional images according to the first coordinate corresponding to each pixel. The second coordinate corresponding to the centroid;

The motion trajectory drawing module is used to establish a coordinate system according to the outline boundary of the target open field in the regional image, and draw the motion trajectory of the experimental animal in the coordinate system according to the second coordinates corresponding to each of the centroids .
The open field experiment data analysis system according to claim 9, wherein the area image interception module comprises:

An area image conversion unit for converting each of the area images into corresponding grayscale images;

A segmentation threshold acquisition unit, configured to acquire an initial segmentation threshold, and convert each of the grayscale images into a corresponding initial binary image according to the initial segmentation threshold;

A binary image judging unit, configured to determine whether the initial binary image satisfies a preset condition;

A binary image determining unit, configured to determine each initial binary image as a binary image corresponding to each video frame if the initial binary image satisfies the preset condition;

The segmentation threshold adjustment unit is configured to adjust the initial segmentation threshold if the initial binarized image does not meet the preset condition, and return to execute converting each of the grayscale images into corresponding ones according to the initial segmentation threshold The initial binary image steps and subsequent steps.
The open field experiment data analysis system according to claim 10, wherein the area image interception module comprises:

A grayscale image display unit for displaying any one of the grayscale images to instruct the user to set the contour boundary corresponding to the target open field according to the displayed grayscale image;

The area image interception unit is configured to intercept the area image corresponding to the target open field from each of the binary images according to the contour boundary.
The open field experiment data analysis system of claim 9, wherein the open field experiment data analysis system further comprises:

A moving distance determining module, configured to determine the moving distance of the experimental animal according to the second coordinates corresponding to each of the centroids;

The moving rate determining module is used to obtain the video duration of the experimental video, and determine the moving rate of the experimental animal according to the moving distance and the video duration.
The open field experimental data analysis system according to any one of claims 9 to 12, wherein the open field experimental data analysis system further comprises:

The target area determination module is configured to determine a target area in the coordinate system, and determine the first number of centroids located in the target area according to the second coordinates corresponding to each of the centroids and the coordinate range corresponding to the target area ；

A centroid quantity determination module, configured to determine a second quantity of the centroid, where the second quantity is the total quantity of centroids included in the motion trajectory;

The video duration acquisition module is used to acquire the video duration of the experimental video;

The activity time determination module is configured to determine the activity time of the experimental animal in the target area according to the video duration, the first quantity and the second quantity.
A terminal device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program as claimed in claims 1 to 8. Any one of the open field experiment data analysis methods.
A computer-readable storage medium, the computer-readable storage medium stores a computer program, wherein the computer program is executed by a processor to realize the open field experiment data according to any one of claims 1 to 8 Analytical method.