Image acquisition method, device and storage medium based on multiple cameras

Abstract

The invention discloses an image acquisition method, device and storage medium based on multiple cameras, relates to the field of image processing, and solves the problem of image delay and frame loss caused by mismatch of communication line performance. The method steps include: the method includes: analyzing the device performance of monitoring devices in a monitoring area, obtaining the device performance level of the monitoring devices, and allocating the transmission capacity of a communication bus in combination with the device performance level; analyzing the color similarity of sample feature images corresponding to the monitoring devices, and obtaining the color similarity coefficient of the sample feature images corresponding to the monitoring devices through analysis; obtaining real-time pixel data of the monitoring devices, and analyzing the refresh rate of the captured images corresponding to the monitoring devices in combination with the real-time pixel data, and obtaining the pixel refresh rate of the captured images corresponding to the monitoring devices through analysis; and performing performance scheduling on the image transmission process of the monitoring devices. The invention realizes adaptive configuration of image acquisition and transmission based on image feature data.

Description

Technical Field

[0001] The present invention belongs to the technical field of image processing, and in particular relates to an image acquisition method, a device and a storage medium based on multiple cameras. Background Art

[0002] The image acquisition technology based on multiple cameras aims to use multiple cameras to capture images simultaneously or collaboratively to obtain more comprehensive and accurate scene information. In practical applications, the field of view can be expanded by deploying multiple cameras at different positions and angles. By capturing different parts of the scene at the same time, multiple cameras can provide a more comprehensive field of view and capture more details and information. However, the synchronization of multiple cameras requires precise time synchronization and image frame synchronization, and image registration and fusion require efficient algorithms and computing resources.

[0003] Under the current technical background, with the upgrading of camera technology, the clarity and fluency of image acquisition have been significantly improved, but it also brings corresponding challenges to the transmission of image data. There is a mismatch between the image captured by high-performance cameras such as high frame rate and high resolution and the performance of communication lines, which leads to delays in image display results, frame loss and other phenomena, thus affecting the normal use of camera equipment. Therefore, how to adaptively configure image acquisition and transmission solutions based on the feature data of the actual acquired images is the current problem;

[0004] To this end, we propose an image acquisition method, device and storage medium based on multiple cameras. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention aims to provide an image acquisition method, device and storage medium based on multiple cameras.

[0006] The technical problems to be solved by the present invention are:

[0007] How to adaptively configure image acquisition and transmission solutions based on image feature data.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions:

[0009] A method for acquiring images based on multiple cameras, the method steps specifically comprising:

[0010] Step S101, obtaining the area configuration information of each monitoring area;

[0011] Step S102, analyzing the device performance of the monitoring device in the monitoring area, analyzing and obtaining the device performance level of the monitoring device, and allocating the transmission capacity of the communication bus in combination with the device performance level;

[0012] Step S103, obtaining a sample feature image of the monitoring device, analyzing the color similarity of the sample feature image corresponding to the monitoring device in combination with the sample feature image, and obtaining a color similarity coefficient of the sample feature image corresponding to the monitoring device;

[0013] Step S104, acquiring real-time pixel data of the monitoring device, analyzing the refresh rate of the corresponding captured image of the monitoring device in combination with the real-time pixel data, and obtaining the pixel refresh rate of the corresponding captured image of the monitoring device through analysis;

[0014] Step S105: performing performance scheduling on the image transmission process of the monitoring device.

[0015] Preferably, the area configuration information includes the number of monitoring devices in the monitoring area and the lens size, lens viewing angle, pixel threshold and image frame number of each monitoring device;

[0016] The real-time pixel data includes the RGB index of each pixel cell in the captured image of the monitoring device, and the collection interval of the real-time pixel data is the standard unit time length.

[0017] Preferably, the analysis process of the device performance of the monitoring device in step S102 is specifically as follows:

[0018] Obtain the number of monitoring devices in the monitoring area and the lens size, lens angle of view, pixel threshold and image frame number of each monitoring device;

[0019] Calculate the equipment performance value of the monitoring equipment, compare the equipment performance value of the monitoring equipment with the equipment performance threshold, and determine the equipment performance level of the corresponding monitoring equipment as the first equipment performance level, the second equipment performance level, or the third equipment performance level; wherein the camera performance of the first equipment performance level is lower than the camera performance of the second equipment performance level, and the camera performance of the second equipment performance level is lower than the camera performance of the third equipment performance level.

[0020] Preferably, the allocation process of the transmission capacity of the communication bus in step S102 is specifically as follows:

[0021] Obtain the equipment performance level of the monitoring equipment in the monitoring area;

[0022] A preset transmission share of the communication bus is allocated to the monitoring devices according to the device performance level.

[0023] Preferably, the corresponding relationship between the transmission share and the device performance level is specifically as follows:

[0024] If the device performance level of the monitoring device is the first device performance level, the preset transmission share of the corresponding monitoring device is the first preset transmission share;

[0025] If the device performance level of the monitoring device is the second device performance level, the preset transmission share of the corresponding monitoring device is the second preset transmission share;

[0026] If the device performance level of the monitoring device is the third device performance level, the preset transmission share of the corresponding monitoring device is the third preset transmission share;

[0027] Among them, the occupancy rate of the first preset transmission share in the communication bus is lower than the occupancy rate of the second preset transmission share in the communication bus, and the occupancy rate of the second preset transmission share in the communication bus is lower than the occupancy rate of the third preset transmission share in the communication bus.

[0028] Preferably, the color similarity analysis process in step S103 is specifically as follows:

[0029] Obtain a sample feature image of the monitoring device, divide the sample feature image into a plurality of pixel cells, and mark the pixel cells as edge cells and center cells according to their positions;

[0030] Obtain the RGB index of any centered cell and the RGB indexes of eight cells adjacent to any centered cell, calculate the color difference coefficient between adjacent cells, and compare the color difference coefficient with the color difference critical value;

[0031] If the color difference coefficient is less than or equal to the color difference critical value, the centered cell and the corresponding cell are determined to be similar cells; if the color difference coefficient is greater than the color difference critical value, the centered cell and the corresponding cell are determined to be non-similar cells;

[0032] The number of similar cells is counted and recorded as the number of similar cells, and then the color similarity coefficient of the sample feature image is calculated.

[0033] Preferably, the analysis process of the pixel refresh rate in step S104 is specifically as follows:

[0034] Obtain the RGB index of each pixel cell in the corresponding captured image of the monitoring device;

[0035] Calculate the pixel refresh rate of the corresponding captured image of the monitoring device.

[0036] Preferably, the scheduling process of performance scheduling in step S105 is specifically as follows:

[0037] Obtaining the color similarity coefficient of the sample feature image corresponding to the monitoring device and the pixel refresh rate of the corresponding captured image;

[0038] Calculate the dispatch demand coefficient of the monitoring equipment, and compare the dispatch demand coefficient of the monitoring equipment with the dispatch demand interval;

[0039] If the scheduling demand coefficient belongs to the first scheduling demand interval, it is determined that the corresponding monitoring device does not need to perform transmission performance scheduling;

[0040] If the scheduling demand coefficient belongs to the second scheduling demand interval, it is determined that the corresponding monitoring device needs to perform transmission performance scheduling, and the idle transmission performance in the communication bus is scheduled in real time;

[0041] Among them, the values ​​of the first scheduling demand interval and the second scheduling demand interval are both greater than zero, and the values ​​of the first scheduling demand interval are both smaller than the values ​​of the second scheduling demand interval.

[0042] The present invention further provides an electronic device, comprising:

[0043] A memory storing a computer program;

[0044] A processor is communicatively connected to the memory, and when the computer program is executed by the processor, an image acquisition method is implemented.

[0045] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the image acquisition method is implemented.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] The present invention first obtains the area configuration information of each monitoring area, and analyzes the equipment performance of the monitoring equipment in the monitoring area, and obtains the equipment performance level of the monitoring equipment through analysis, and allocates the transmission capacity of the communication bus in combination with the equipment performance level, and then obtains the sample feature image of the monitoring equipment, and analyzes the color similarity of the sample feature image corresponding to the monitoring equipment in combination with the sample feature image, and obtains the color similarity coefficient of the sample feature image corresponding to the monitoring equipment through analysis, and further obtains the real-time pixel data of the monitoring equipment, and analyzes the refresh rate of the captured image corresponding to the monitoring equipment in combination with the real-time pixel data, and obtains the pixel refresh rate of the captured image corresponding to the monitoring equipment through analysis, and finally performs performance scheduling on the image transmission process of the monitoring equipment. The present invention realizes adaptive configuration of image acquisition and transmission based on image feature data. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0049] Figure 1 is a flow chart of the method of the present invention;

[0050] Figure 2 It is a connection schematic diagram of the present invention;

[0051] Figure 3 It is a principle schematic diagram of the data acquisition module in the present invention;

[0052] Figure 4 is a schematic diagram of the operation of the image analysis module in the present invention;

[0053] Figure 5 Schematic diagram of the principle of the image analysis module in the present invention;

[0054] Figure 6 It is a schematic diagram of the structure of the electronic device in the present invention. DETAILED DESCRIPTION

[0055] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] Example 1: Please refer to Figure 1-Figure 5 As shown, the technical solution provided by the present invention is: a method for acquiring images based on multiple cameras, the application scenarios include indoor, corridor, road traffic and various complex scenarios. In this embodiment, the application scenarios are divided into several monitoring areas. In the actual working process, several monitoring devices are arranged in the monitoring area. The monitoring devices transmit image information to the communication terminal through the communication bus. The communication terminal is connected to the display matrix. It can be understood that the monitoring devices and the displays in the display matrix are in a one-to-one correspondence, that is, the monitoring device serial number and the camera serial number are always consistent;

[0057] In this embodiment, the steps of the image acquisition method specifically include:

[0058] Step S101, obtaining the area configuration information of each monitoring area;

[0059] like Figure 3 As shown, the area configuration information includes the number of monitoring devices in the monitoring area and the lens size, lens angle, pixel critical value and image frame number of each monitoring device, where the pixel critical value is the maximum pixel value of the monitoring device participating in photosensitive imaging, and the image frame number is the number of images recorded by the monitoring device per second, usually in fps (frames per second).

[0060] Step S102, analyzing the device performance of the monitoring device in the monitoring area, analyzing and obtaining the device performance level of the monitoring device, and allocating the transmission capacity of the communication bus in combination with the device performance level;

[0061] In this embodiment, the analysis process of the device performance of the monitoring device in step S102 is specifically as follows:

[0062] Get the number of monitoring devices I in the monitoring area and the lens size JTi, lens angle SJi, pixel critical value XSi and image frame number ZSi of each monitoring device, where i is the monitoring device serial number and the upper limit value of i is 1;

[0063] The equipment performance value XNi of the monitoring equipment is calculated according to the formula. The specific formula is as follows:

[0064] XNi=(JTi*SJi)*s1+(XSi*ZSi)*s2;

[0065] Among them, s1 and s2 are weight coefficients with fixed values, the values ​​of s1 and s2 are both greater than zero and s1+s2=1, s1 is the monitoring range weight, and s2 is the image quality weight;

[0066] Compare the device performance value of the monitoring device with the device performance threshold;

[0067] If the device performance value is less than or equal to the first device performance threshold, the device performance level of the corresponding monitoring device is determined to be the first device performance level;

[0068] If the device performance value is greater than the first device performance threshold and less than or equal to the second device performance threshold, the device performance level of the corresponding monitoring device is determined to be the second device performance level;

[0069] If the device performance value is greater than the second device performance threshold, the device performance level of the corresponding monitoring device is determined to be the third device performance level;

[0070] Wherein, the values ​​of the first device performance threshold and the second device performance threshold are both greater than zero, the first device performance threshold is less than the second device performance threshold, the camera performance of the first device performance level is lower than the camera performance of the second device performance level, and the camera performance of the second device performance level is lower than the camera performance of the third device performance level;

[0071] It is understandable that the higher the performance level of the monitoring device, the higher the quality and frame rate of the recorded image or video, so that the monitoring device needs to occupy more transmission capacity of the communication bus when transmitting images;

[0072] Furthermore, the allocation process of the transmission capacity of the communication bus in step S102 is specifically as follows:

[0073] Obtaining the device performance level of the monitoring device in the monitoring area, and allocating the preset transmission share of the communication bus to the monitoring device according to the device performance level, wherein the corresponding relationship between the transmission share and the device performance level is specifically as follows;

[0074] If the device performance level of the monitoring device is the first device performance level, the preset transmission share of the corresponding monitoring device is the first preset transmission share;

[0075] If the device performance level of the monitoring device is the second device performance level, the preset transmission share of the corresponding monitoring device is the second preset transmission share;

[0076] If the device performance level of the monitoring device is the third device performance level, the preset transmission share of the corresponding monitoring device is the third preset transmission share;

[0077] Among them, the occupancy rate of the first preset transmission share in the communication bus is lower than the occupancy rate of the second preset transmission share in the communication bus, and the occupancy rate of the second preset transmission share in the communication bus is lower than the occupancy rate of the third preset transmission share in the communication bus. In the actual working process, if the sum of the preset transmission shares corresponding to the monitoring devices in the monitoring area exceeds the communication bus tolerance threshold, the communication bus is subjected to transmission performance improvement operation.

[0078] As a further solution of this embodiment, after completing the preliminary configuration of the monitoring device and the pass bus;

[0079] Step S103, obtaining a sample feature image of the monitoring device, analyzing the color similarity of the sample feature image corresponding to the monitoring device in combination with the sample feature image, and obtaining a color similarity coefficient of the sample feature image corresponding to the monitoring device;

[0080] In this embodiment, the monitoring device acquires the sample feature image of the monitoring device according to a preset monitoring period. For example, if the monitoring period of the monitoring device is 1 hour and the start time of the monitoring device is 8:00am, the monitoring device samples the sample feature image once at 8:00am, 9:00am and 10:00am respectively. By 10:00am, the monitoring device performs a total of three sample feature image sampling operations;

[0081] like Figure 4 and Figure 5 As shown, the analysis process of color similarity in step S103 is specifically as follows:

[0082] Obtain a sample feature image of the monitoring device and divide the sample feature image into m×n pixel cells, such as Figure 5 As shown, the pixel cells are marked as edge cells and center cells according to their positions. It can be understood that m is the total number of rows of pixel cells, n is the total number of columns of pixel cells, the number of edge cells is [2m+2(n-2)], and the number of center cells is (m-2)×(n-2);

[0083] Get the RGB index (Rir, Gir, Bir) of any centered cell, as well as the RGB index of the eight cells adjacent to any centered cell, and calculate the color difference coefficients SCir1 to SCir8 between adjacent cells using the formula, where r is the centered cell number, and the position arrangement of ri1 to ri8 is specifically referred to Figure 5 As shown, the formula is as follows:

[0084] ;

[0085] Among them, (Rir1, Gir1, Bir1) is the RGB index of the center cell corresponding to cell number one;

[0086] Similarly, , (Rir2, Gir2, Bir2) are the RGB indices of the centered cell corresponding to the second cell;

[0087] Compare the color difference coefficients SCir1 to SCir8 with the color difference critical value;

[0088] If the color difference coefficient is less than or equal to the color difference critical value, the center cell and the corresponding cell are determined to be similar cells;

[0089] If the color difference coefficient is greater than the color difference critical value, the center cell and the corresponding cell are determined to be non-similar cells;

[0090] Wherein, the value of the color difference critical value is greater than zero, and the color difference critical value is pre-stored in the database;

[0091] The color similarity coefficient DDi of the sample feature image is calculated according to the formula, which is as follows:

[0092] ;

[0093] Among them, XNir is the number of similar cells corresponding to each centered cell, the number of similar cells + the number of non-similar cells = 8, and the upper limit value of r is R, which is equal to the number of centered cells.

[0094] Step S104, simultaneously acquiring real-time pixel data of the monitoring device, analyzing the refresh rate of the corresponding captured image of the monitoring device in combination with the real-time pixel data, and analyzing to obtain the pixel refresh rate of the corresponding captured image of the monitoring device;

[0095] The real-time pixel data includes the RGB index of each pixel unit in the captured image of the monitoring device. The collection interval of the real-time pixel data is the standard unit time length. In this embodiment, the standard unit time length is 1s;

[0096] The analysis process of the pixel refresh rate in step S104 is specifically as follows:

[0097] Get the RGB index (Rit, Git, Bit) of each pixel cell in the captured image corresponding to the monitoring device, where t is the pixel cell serial number, t is a non-zero natural number, the upper limit of t is T, and the value of T is equal to the number of pixel cells in the captured image;

[0098] The pixel refresh rate SXi of the corresponding captured image of the monitoring device is calculated according to the formula. The specific formula is as follows:

[0099] ;

[0100] Among them, (Rit', Git', Bit') and (Rit, Git, Bit) are the RGB indices of pixel cell t at adjacent moments, and the interval between adjacent moments is equal to the standard unit duration.

[0101] Step S105, performing performance scheduling on the image transmission process of the monitoring device;

[0102] In this embodiment, the scheduling process of performance scheduling is as follows:

[0103] Obtain the color similarity coefficient of the sample feature image corresponding to the monitoring device and the pixel refresh rate of the corresponding captured image, and calculate the scheduling demand coefficient XQi of the monitoring device according to the formula. The specific formula is as follows:

[0104] XQi=a1 / DDi+SXi×a2; where a1 and a2 are weight coefficients with fixed values, and the values ​​of a1 and a2 are both greater than zero, a1 is the image richness weight, and a2 is the image refresh rate weight. It can be understood that the smaller the value of the color similarity description, the larger the value of the pixel refresh rate, and the greater the performance requirement of the monitoring equipment for image transmission, that is, the greater the value of the scheduling demand coefficient;

[0105] Compare the dispatch demand coefficient of the monitoring equipment with the dispatch demand interval;

[0106] If the scheduling demand coefficient belongs to the first scheduling demand interval, it is determined that the corresponding monitoring device does not need to perform transmission performance scheduling;

[0107] If the scheduling demand coefficient belongs to the second scheduling demand interval, it is determined that the corresponding monitoring device needs to perform transmission performance scheduling, and the idle transmission performance in the communication bus is scheduled in real time;

[0108] Among them, the values ​​of the first scheduling demand interval and the second scheduling demand interval are both greater than zero, and the values ​​of the first scheduling demand interval are both smaller than the values ​​of the second scheduling demand interval.

[0109] Embodiment 2: Different from Embodiment 1, the image acquisition method based on multiple cameras further includes:

[0110] Step S106, obtaining historical monitoring data and real-time environmental data of the monitoring area, analyzing the equipment configuration of the monitoring area in combination with the historical monitoring data and the real-time environmental data, and generating a monitoring adjustment signal according to the analysis result to adjust the configuration of the monitoring equipment in the monitoring area;

[0111] Among them, the historical monitoring data includes the number of historical alarms in the monitoring area, the size of the monitoring area and the number of regional marking points. The historical monitoring data of the monitoring area can be obtained from the database. The number of historical alarms is the number of records of events detected by the monitoring equipment and alarms in the corresponding monitoring area in the past quarter. The size of the monitoring area is the spatial size of the monitoring area, that is, the product of the spatial length, spatial width and spatial height of the monitoring area. The number of regional marking points is the number of marking points in the monitoring area. The marking points are manually calibrated or changed. For example, the valuables stacking place, the dangerous goods stacking place and the entrance and exit of the monitoring area are points in the monitoring area that need to be monitored;

[0112] The real-time environmental data includes the real-time regional temperature and real-time regional humidity of the monitoring area. In this embodiment, the real-time regional temperature of the monitoring area is obtained by a thermometer, and the real-time regional humidity of the monitoring area is obtained by a humidity sensor;

[0113] The specific process of analyzing the device configuration of the monitoring area in step S106 is as follows:

[0114] Obtain the historical alarm count BJ, the monitoring area size GM and the number of regional marking points BD of the monitoring area, and calculate the regional risk coefficient FX of the monitoring area according to the formula. The specific formula is as follows:

[0115] FX = BJ × b1 + GM × b2 + BD × b3;

[0116] Among them, b1, b2 and b3 are proportional coefficients with fixed values, and the values ​​of b1, b2 and b3 are all greater than zero;

[0117] Obtain the real-time regional temperature ST and real-time regional humidity SW of the monitoring area, and calculate the environmental risk coefficient HJ of the monitoring area according to the formula. The specific formula is as follows:

[0118] HJ=|ST-BT|×c1+|SW-BW|×c2; where BT is the standard area temperature, BW is the standard area humidity, c1 and c2 are weight coefficients with fixed values, c1 is the temperature deviation weight, and c2 is the humidity deviation weight;

[0119] Compare the regional risk factor and environmental risk factor of the monitored area with the critical risk factor;

[0120] If the regional risk factor of the monitored area is greater than or equal to the critical risk factor or the environmental risk factor of the monitored area is greater than or equal to the critical risk factor, a monitoring adjustment signal is generated;

[0121] If the regional risk factor of the monitored area is less than the critical risk factor and the environmental risk factor of the monitored area is less than the critical risk factor, no action is taken;

[0122] It should be specified that configuration adjustment specifically includes measures such as increasing the number of monitoring devices in the monitoring area, increasing the monitoring angle of the monitoring devices, and shortening the rotation period of the monitoring devices;

[0123] In this application, if corresponding calculation formulas appear, the above calculation formulas are all dimensionless and take their numerical calculations. The weight coefficients, proportional coefficients and other coefficients in the formulas are set to a result value obtained by quantifying each parameter. The size of the weight coefficient and the proportional coefficient can be determined as long as it does not affect the proportional relationship between the parameter and the result value.

[0124] Embodiment 3: Figure 6 The structural schematic diagram of an electronic device is illustrated, and the electronic device may include: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus. The processor may call the logic instructions in the memory to execute an image acquisition method based on multiple cameras, and the method includes: obtaining the regional configuration information of each monitoring area; analyzing the equipment performance of the monitoring equipment in the monitoring area, analyzing to obtain the equipment performance level of the monitoring equipment, and allocating the transmission capacity of the communication bus in combination with the equipment performance level; obtaining the sample feature image of the monitoring equipment, analyzing the color similarity of the sample feature image corresponding to the monitoring equipment in combination with the sample feature image, and analyzing to obtain the color similarity coefficient of the sample feature image corresponding to the monitoring equipment; obtaining the real-time pixel data of the monitoring equipment, analyzing the refresh rate of the captured image corresponding to the monitoring equipment in combination with the real-time pixel data, and analyzing to obtain the pixel refresh rate of the captured image corresponding to the monitoring equipment; performing performance scheduling on the image transmission process of the monitoring equipment; obtaining the historical monitoring data and real-time environmental data of the monitoring area, analyzing the equipment configuration of the monitoring area in combination with the historical monitoring data and the real-time environmental data, and generating a monitoring adjustment signal according to the analysis result to adjust the configuration of the monitoring equipment in the monitoring area.

[0125] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable an electronic device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0126] Embodiment 4: The present application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute a multi-camera image acquisition method provided by the above methods, which includes: obtaining area configuration information of each monitoring area; analyzing the equipment performance of the monitoring equipment in the monitoring area, analyzing to obtain the equipment performance level of the monitoring equipment, and allocating the transmission capacity of the communication bus in combination with the equipment performance level; obtaining a sample feature image of the monitoring equipment, analyzing the color similarity of the sample feature image corresponding to the monitoring equipment in combination with the sample feature image, and analyzing to obtain the color similarity coefficient of the sample feature image corresponding to the monitoring equipment; obtaining real-time pixel data of the monitoring equipment, analyzing the refresh rate of the captured image corresponding to the monitoring equipment in combination with the real-time pixel data, and analyzing to obtain the pixel refresh rate of the captured image corresponding to the monitoring equipment; performing performance scheduling on the image transmission process of the monitoring equipment; obtaining historical monitoring data and real-time environmental data of the monitoring area, analyzing the equipment configuration of the monitoring area in combination with the historical monitoring data and the real-time environmental data, and generating a monitoring adjustment signal based on the analysis result to adjust the configuration of the monitoring equipment in the monitoring area.

[0127] Embodiment 5: The present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the above-mentioned image acquisition method based on multiple cameras, the method comprising: obtaining the area configuration information of each monitoring area; analyzing the equipment performance of the monitoring equipment in the monitoring area, analyzing to obtain the equipment performance level of the monitoring equipment, and allocating the transmission capacity of the communication bus in combination with the equipment performance level; obtaining the sample feature image of the monitoring equipment, analyzing the color similarity of the sample feature image corresponding to the monitoring equipment in combination with the sample feature image, and obtaining the color similarity coefficient of the sample feature image corresponding to the monitoring equipment; obtaining the real-time pixel data of the monitoring equipment, analyzing the refresh rate of the captured image corresponding to the monitoring equipment in combination with the real-time pixel data, and obtaining the pixel refresh rate of the captured image corresponding to the monitoring equipment; performing performance scheduling on the image transmission process of the monitoring equipment; obtaining the historical monitoring data and real-time environmental data of the monitoring area, analyzing the equipment configuration of the monitoring area in combination with the historical monitoring data and the real-time environmental data, and generating a monitoring adjustment signal based on the analysis result to adjust the configuration of the monitoring equipment in the monitoring area.

[0128] The device embodiments described above are merely illustrative, wherein 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 modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0129] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for an electronic device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0130] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for acquiring an image based on multiple cameras, characterized in that: The method steps specifically include: Step S101, obtaining the area configuration information of each monitoring area; Step S102, analyzing the device performance of the monitoring device in the monitoring area, analyzing and obtaining the device performance level of the monitoring device, and allocating the transmission capacity of the communication bus in combination with the device performance level; The analysis process of the device performance of the monitoring device in step S102 is specifically as follows: Get the number of monitoring devices I in the monitoring area and the lens size JTi, lens angle SJi, pixel critical value XSi and image frame number ZSi of each monitoring device, where i is the monitoring device serial number and the upper limit value of i is 1; The equipment performance value XNi of the monitoring equipment is calculated according to the formula. The specific formula is as follows: XNi=(JTi*SJi)*s1+(XSi*ZSi)*s2;wherein, s1 and s2 are weight coefficients with fixed values, the values ​​of s1 and s2 are both greater than zero and s1+s2=1, s1 is the monitoring range weight, and s2 is the image quality weight; Comparing the device performance value of the monitoring device with the device performance threshold, determining the device performance level of the corresponding monitoring device as the first device performance level, the second device performance level, or the third device performance level; wherein the camera performance of the first device performance level is lower than the camera performance of the second device performance level, and the camera performance of the second device performance level is lower than the camera performance of the third device performance level; The specific process of allocating the transmission capacity of the communication bus in step S102 is as follows: Obtain the equipment performance level of the monitoring equipment in the monitoring area; The preset transmission share of the communication bus is allocated to the monitoring device according to the device performance level, and the corresponding relationship between the transmission share and the device performance level is specifically as follows; If the device performance level of the monitoring device is the first device performance level, the preset transmission share of the corresponding monitoring device is the first preset transmission share; If the device performance level of the monitoring device is the second device performance level, the preset transmission share of the corresponding monitoring device is the second preset transmission share; If the device performance level of the monitoring device is the third device performance level, the preset transmission share of the corresponding monitoring device is the third preset transmission share; The occupancy rate of the first preset transmission share in the communication bus is lower than the occupancy rate of the second preset transmission share in the communication bus, and the occupancy rate of the second preset transmission share in the communication bus is lower than the occupancy rate of the third preset transmission share in the communication bus; Step S103, obtaining a sample feature image of the monitoring device, analyzing the color similarity of the sample feature image corresponding to the monitoring device in combination with the sample feature image, and obtaining a color similarity coefficient of the sample feature image corresponding to the monitoring device; The color similarity analysis process in step S103 is specifically as follows: Obtain a sample feature image of the monitoring device, divide the sample feature image into m×n pixel cells, and mark the pixel cells as edge cells and center cells according to their positions; m is the total number of rows of pixel cells, n is the total number of columns of pixel cells, the number of edge cells is [2m+2(n-2)], and the number of center cells is (m-2)×(n-2); Get the RGB index (Rir, Gir, Bir) of any centered cell and the RGB index of eight cells adjacent to any centered cell, and calculate the color difference coefficients SCir1 to SCir8 between adjacent cells by formula, where r is the centered cell number; ； Among them, (Rir1, Gir1, Bir1) is the RGB index of the center cell corresponding to cell number one; Similarly, , (Rir2, Gir2, Bir2) are the RGB indices of the centered cell corresponding to the second cell; Compare the color difference coefficients SCir1 to SCir8 with the color difference critical value; If the color difference coefficient is less than or equal to the color difference critical value, the centered cell and the corresponding cell are determined to be similar cells; if the color difference coefficient is greater than the color difference critical value, the centered cell and the corresponding cell are determined to be non-similar cells; The number of similar cells is counted and recorded as the number of similar cells, and then the color similarity coefficient DDi of the sample feature image is calculated according to the formula. The specific formula is as follows: ; Where XNir is the number of similar cells corresponding to each centered cell, the number of similar cells + the number of non-similar cells = 8, the upper limit of r is R, and R is equal to the number of centered cells; Step S104, acquiring real-time pixel data of the monitoring device, analyzing the refresh rate of the corresponding captured image of the monitoring device in combination with the real-time pixel data, and obtaining the pixel refresh rate of the corresponding captured image of the monitoring device through analysis; The analysis process of the pixel refresh rate in step S104 is specifically as follows: Get the RGB index (Rit, Git, Bit) of each pixel cell in the captured image corresponding to the monitoring device, where t is the pixel cell serial number, t is a non-zero natural number, the upper limit of t is T, and the value of T is equal to the number of pixel cells in the captured image; The pixel refresh rate SXi of the corresponding captured image of the monitoring device is calculated according to the formula. The specific formula is as follows: ； Among them, (Rit', Git', Bit') and (Rit, Git, Bit) are the RGB indices of pixel cell t at adjacent moments, and the interval between adjacent moments is equal to the standard unit duration; Step S105, performing performance scheduling on the image transmission process of the monitoring device; The performance scheduling process in step S105 is specifically as follows: Obtaining the color similarity coefficient of the sample feature image corresponding to the monitoring device and the pixel refresh rate of the corresponding captured image; The dispatch demand coefficient XQi of the monitoring equipment is calculated according to the formula. The specific formula is as follows: XQi=a1 / DDi+SXi×a2; where a1 and a2 are weight coefficients with fixed values, and the values ​​of a1 and a2 are both greater than zero, a1 is the image richness weight, and a2 is the image refresh rate weight; Compare the dispatch demand coefficient of the monitoring equipment with the dispatch demand interval; If the scheduling demand coefficient belongs to the first scheduling demand interval, it is determined that the corresponding monitoring device does not need to perform transmission performance scheduling; If the scheduling demand coefficient belongs to the second scheduling demand interval, it is determined that the corresponding monitoring device needs to perform transmission performance scheduling, and the idle transmission performance in the communication bus is scheduled in real time; Among them, the values ​​of the first scheduling demand interval and the second scheduling demand interval are both greater than zero, and the values ​​of the first scheduling demand interval are both smaller than the values ​​of the second scheduling demand interval.

2. The method for acquiring images based on multiple cameras according to claim 1, characterized in that: The regional configuration information includes the number of monitoring devices in the monitoring area and the lens size, lens viewing angle, pixel threshold and image frame number of each monitoring device; The real-time pixel data includes the RGB index of each pixel cell in the captured image of the monitoring device, and the collection interval of the real-time pixel data is the standard unit time length.

3. An electronic device, characterized in that: The electronic device comprises: a memory storing a computer program; A processor is communicatively connected to the memory, and when the computer program is executed by the processor, the image acquisition method described in any one of claims 1-2 is implemented.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the image acquisition method described in any one of claims 1 to 2 is implemented.

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