A video anti-shake analysis system for vehicle-mounted control ball

Abstract

The present invention belongs to the field of video anti-shake, and relates to data analysis technology, and is used to solve the problem that the video anti-shake analysis system for a vehicle-mounted control ball in the prior art cannot provide an optimization direction for a vehicle-mounted control ball with unqualified anti-shake performance according to test data. Specifically, the present invention is a video anti-shake analysis system for a vehicle-mounted control ball, comprising a test simulation module, a jitter analysis module, a jitter evaluation module, and an adaptive optimization module; the test simulation module is used to perform video jitter test analysis on the vehicle-mounted control ball: generate a plurality of simulated test environments, and then perform jitter tests on a test vehicle and a reference vehicle in the simulated test environments to obtain a plurality of test processes; the present invention can perform video jitter test analysis on the vehicle-mounted control ball, and generate a plurality of simulated test environments for the vehicle-mounted control ball, wherein the height and distance interval of obstacles in each simulated test environment are different, and the comprehensiveness and accuracy of the jitter test results are improved.

Description

Technical Field

[0001] The invention belongs to the field of video anti-shake, relates to data analysis technology, and specifically is a video anti-shake analysis system for a vehicle-mounted control ball. Background Art

[0002] With the rapid development of modern intelligent transportation systems, vehicle-mounted surveillance cameras are used as an important monitoring device. In practical applications, the videos taken by vehicle-mounted surveillance cameras are often affected by jitter, resulting in unstable images and affecting the observation effect. Therefore, it is of great significance to study the video anti-shake technology of vehicle-mounted surveillance cameras.

[0003] The existing video stabilization analysis system for the vehicle-mounted control ball is unable to test and analyze the video stabilization performance of the vehicle-mounted control ball, nor can it provide optimization direction for the vehicle-mounted control ball with unqualified stabilization performance based on the test data, resulting in the inability to ensure video stability.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a video anti-shake analysis system for a vehicle-mounted control ball, which is used to solve the problem that the video anti-shake analysis system for a vehicle-mounted control ball in the prior art cannot provide an optimization direction for a vehicle-mounted control ball with unqualified anti-shake performance according to test data;

[0006] The technical problem to be solved by the present invention is: how to provide a video anti-shake analysis system for a vehicle-mounted control ball that can provide an optimization direction for a vehicle-mounted control ball with unqualified anti-shake performance according to test data.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A video anti-shake analysis system for a vehicle-mounted control ball, comprising a test simulation module, a jitter analysis module, a jitter evaluation module and an adaptive optimization module, wherein the test simulation module, the jitter analysis module, the jitter evaluation module and the adaptive optimization module are sequentially connected in communication;

[0009] The test simulation module is used to perform video jitter test analysis on the vehicle-mounted control ball: generate several simulated test environments, set the driving speed of the test vehicle and the reference vehicle to M1 kilometers per hour, and then perform jitter tests on the test vehicle and the reference vehicle in the simulated test environment to obtain several test processes;

[0010] The jitter analysis module is used to perform jitter analysis on the test process: during the test process, a video is recorded by a vehicle-mounted control ball and the obtained video is decomposed into test images frame by frame, and the position information of the reference vehicle in the test image is extracted; the position information of the reference vehicle in the test image is compared with the position information of the reference vehicle in the previous test image to obtain the offset coefficient of the test image, and then the offset coefficients of all test images are numerically calculated to obtain the jitter coefficient DD of the test process, and the jitter coefficients DD of all test processes are sent to the jitter evaluation module;

[0011] The jitter evaluation module is used to evaluate and analyze the video jitter state of the vehicle-mounted control ball and obtain the jitter performance value and jitter stability value of the vehicle-mounted control ball, and determine whether the video jitter state of the vehicle-mounted control ball meets the requirements through the jitter performance value and the jitter stability value;

[0012] The adaptation optimization module is used to optimize the adaptability of the vehicle-mounted control ball.

[0013] Furthermore, the simulated test environment includes: setting L1 speed bumps on the test road, the height value of each speed bump and the distance interval between adjacent speed bumps are randomly set, installing the on-board control ball on the test vehicle, and then setting a reference vehicle in front of the test vehicle, and the driving direction of the reference vehicle is the same as that of the test vehicle.

[0014] Furthermore, the position information extraction process includes: setting a number of reference points on the reference vehicle, extracting the coordinates of the reference points of the reference vehicle in the test image, and then forming the position information from the coordinates of all the reference points.

[0015] Furthermore, the process of obtaining the offset coefficient of the test image includes: marking the absolute value of the difference in the horizontal coordinates of the same reference point in the two test images as the horizontal offset value, marking the absolute value of the difference in the vertical coordinates of the same reference point in the two test images as the vertical offset value, marking the sum of the horizontal offset value and the vertical offset value as the overall offset value of the reference point, and summing and averaging the overall offset values ​​of all reference points to obtain the offset coefficient of the test image.

[0016] Furthermore, the process of obtaining the jitter coefficient DD includes: summing up the offset coefficients of all test images and taking the average value to obtain the offset mean PJ of the test process, marking the maximum value of the offset coefficients in all test images as the offset prominent value PT of the test process, and performing numerical calculation on the offset mean PJ and the offset prominent value PT to obtain the jitter coefficient DD of the test process.

[0017] Furthermore, the process of obtaining the jitter performance value and jitter stability value of the vehicle-mounted control ball includes: summing up the jitter coefficients DD of all test processes and taking the average value to obtain the jitter performance value of the vehicle-mounted control ball, and performing variance calculation on the jitter coefficients DD of all test processes to obtain the jitter stability value of the vehicle-mounted control ball.

[0018] Furthermore, the specific process of determining whether the video jitter state of the vehicle-mounted control ball meets the requirements includes: comparing the jitter performance value and the jitter stability value of the vehicle-mounted control ball with the preset jitter performance threshold and the jitter stability threshold respectively: if the jitter performance value is less than the jitter performance threshold and the jitter stability value is less than the jitter stability threshold, then it is determined that the video jitter state of the vehicle-mounted control ball meets the requirements; if the jitter performance value is greater than or equal to the jitter performance threshold, then it is determined that the video jitter state of the vehicle-mounted control ball does not meet the requirements, a performance abnormality signal is generated and the performance abnormality signal is sent to the mobile phone terminal of the administrator; if the jitter performance value is less than the jitter performance threshold and the jitter stability value is greater than or equal to the jitter stability threshold, then it is determined that the anti-shake adaptability of the vehicle-mounted control ball does not meet the requirements, an adaptation optimization signal is generated and the adaptation optimization signal is sent to the adaptation optimization module.

[0019] Furthermore, the specific process of the adaptive optimization module optimizing the adaptability of the vehicle-mounted control ball includes: marking the test process in which the jitter coefficient DD is not less than the jitter performance threshold as an optimization process, dividing the optimization process into several optimization periods, obtaining the maximum jitter amplitude and the maximum jitter frequency of the vehicle-mounted control ball mirror during the optimization period and marking them as the jitter amplitude value DF and the jitter frequency value DP respectively, and obtaining the mechanical jitter value JD of the optimization period by numerically calculating the jitter amplitude value DF and the jitter frequency value DP; summing and averaging the mechanical jitter values ​​JD of all optimization periods to obtain the mechanical optimization coefficient of the optimization process, and comparing the mechanical optimization coefficient with the mechanical optimization threshold: if the mechanical optimization coefficient is less than the mechanical optimization threshold, then generating an algorithm optimization signal and sending the algorithm optimization signal to the mobile phone terminal of the manager; if the mechanical optimization coefficient is greater than or equal to the mechanical optimization threshold, then generating a mechanical optimization signal and sending the mechanical optimization signal to the mobile phone terminal of the manager.

[0020] The present invention has the following beneficial effects:

[0021] 1. The test simulation module can be used to perform video jitter test analysis on the vehicle-mounted control ball, and multiple simulation test environments can be generated for the vehicle-mounted control ball. The height and distance interval of obstacles in each simulation test environment are different, thereby providing multiple sample data for jitter test and improving the comprehensiveness and accuracy of jitter test results;

[0022] 2. The jitter analysis module can be used to analyze the jitter of the test process. After decomposing the video, the jitter coefficient is obtained by comparing the test image with the reference vehicle position information. The jitter degree of the video of the vehicle-mounted control ball during the test process is fed back according to the jitter coefficient.

[0023] 3. The jitter evaluation module can evaluate and analyze the video jitter status of the vehicle-mounted control ball. According to the calculated jitter performance value and jitter stability value, the overall video jitter status of the vehicle-mounted control ball during all tests can be evaluated, and timely feedback can be given when the video jitter status of the vehicle-mounted control ball is unqualified;

[0024] 4. The adaptability of the vehicle-mounted control ball can be optimized and analyzed through the adaptive optimization module, the optimization process can be screened, and then the mirror jitter parameters of the vehicle-mounted control ball during the optimization process can be extracted and analyzed to obtain the mechanical optimization coefficient, so as to make a decision analysis on the video anti-shake optimization direction of the vehicle-mounted control ball through the value of the mechanical optimization coefficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0027] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0028] 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, rather than 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.

[0029] Embodiment 1

[0030] like Figure 1 As shown, a video anti-shake analysis system for a vehicle-mounted control ball includes a test simulation module, a jitter analysis module, a jitter evaluation module and an adaptive optimization module. The test simulation module, the jitter analysis module, the jitter evaluation module and the adaptive optimization module are communicatively connected in sequence.

[0031] The test simulation module is used to perform video jitter test analysis on the vehicle-mounted control ball: generate several simulated test environments, the simulated test environment includes: setting L1 speed bumps on the test road, the height value of each speed bump and the distance interval between adjacent speed bumps are randomly set, the vehicle-mounted control ball is installed on the test vehicle, and then a reference vehicle is set in front of the test vehicle. The driving direction of the reference vehicle is the same as that of the test vehicle, and the driving speeds of the test vehicle and the reference vehicle are set to M1 kilometers per hour. L1 and M1 are both numerical constants, and the specific values ​​of L1 and M1 are set by the management personnel; then the test vehicle and the reference vehicle are subjected to jitter test in the simulated test environment to obtain several test processes; video jitter test analysis is performed on the vehicle-mounted control ball, and multiple simulated test environments are generated for the vehicle-mounted control ball. The height and distance interval of obstacles in each simulated test environment are different, thereby providing multiple sample data for the jitter test and improving the comprehensiveness and accuracy of the jitter test results.

[0032] The jitter analysis module is used to perform jitter analysis on the test process: during the test, the vehicle-mounted control ball is used to record the video and decompose the obtained video into test images frame by frame, and the position information of the reference vehicle in the test image is extracted. The position information extraction process includes: setting a number of reference points on the reference vehicle, extracting the coordinates of the reference points of the reference vehicle in the test image, and then forming the position information from the coordinates of all the reference points; comparing the position information of the reference vehicle in the test image with the position information of the reference vehicle in the previous frame of the test image: marking the absolute value of the difference between the horizontal coordinates of the same reference point in the two test images as the horizontal offset value, marking the absolute value of the difference between the vertical coordinates of the same reference point in the two test images as the longitudinal offset value, and marking the sum of the horizontal offset value and the longitudinal offset value as the reference point. The overall offset value is obtained by summing up and averaging the overall offset values ​​of all reference points to obtain the offset coefficient of the test image; then the offset coefficients of all test images are summed up and averaged to obtain the offset mean PJ of the test process, and the maximum value of the offset coefficient in all test images is marked as the offset prominent value PT of the test process; the jitter coefficient DD of the test process is obtained by the formula DD=k1*PJ+k2*PT, where k1 and k2 are both proportional coefficients, and k1>k2>1; the jitter coefficient DD of all test processes is sent to the jitter evaluation module; the test process is subjected to jitter analysis, and after the video is decomposed, the test image is compared with the reference vehicle position information to obtain the jitter coefficient, and the video jitter degree of the vehicle-mounted control ball during the test process is fed back according to the jitter coefficient.

[0033] The jitter evaluation module is used to evaluate and analyze the video jitter status of the vehicle-mounted control ball: the jitter coefficients DD of all test processes are summed and averaged to obtain the jitter performance value of the vehicle-mounted control ball, and the variance of the jitter coefficients DD of all test processes is calculated to obtain the jitter stability value of the vehicle-mounted control ball. The jitter performance value and jitter stability value of the vehicle-mounted control ball are compared with the preset jitter performance threshold and jitter stability threshold respectively: if the jitter performance value is less than the jitter performance threshold and the jitter stability value is less than the jitter stability threshold, it is determined that the video jitter status of the vehicle-mounted control ball meets the requirements; if the jitter performance value is greater than or equal to the jitter performance threshold, it is determined that the vehicle-mounted control ball meets the requirements; if the jitter performance value is greater than or equal to the jitter performance threshold, it is determined that the vehicle-mounted control ball meets the requirements. If the video jitter state of the vehicle-mounted control ball does not meet the requirements, a performance abnormality signal is generated and sent to the mobile terminal of the administrator; if the jitter performance value is less than the jitter performance threshold and the jitter stability value is greater than or equal to the jitter stability threshold, it is determined that the anti-shake adaptability of the vehicle-mounted control ball does not meet the requirements, and an adaptation optimization signal is generated and sent to the adaptation optimization module; the video jitter state of the vehicle-mounted control ball is evaluated and analyzed, and the overall video jitter state of the vehicle-mounted control ball during all test processes is evaluated according to the calculated jitter performance value and jitter stability value, and timely feedback is provided when the video jitter state of the vehicle-mounted control ball is unqualified.

[0034] The adaptive optimization module is used to optimize the adaptability of the vehicle-mounted control ball: the test process in which the jitter coefficient DD is not less than the jitter performance threshold is marked as the optimization process, and the optimization process is divided into several optimization periods. The maximum jitter amplitude and the maximum jitter frequency of the vehicle-mounted control ball mirror in the optimization period are obtained and marked as the jitter amplitude value DF and the jitter frequency value DP respectively. The mechanical jitter value JD of the optimization period is obtained by the formula JD=u1*DF+u2*DP, where u1 and u2 are both proportional coefficients, and u1>u2>1; the mechanical jitter values ​​JD of all optimization periods are summed and averaged to obtain the mechanical optimization coefficient of the optimization process. , compare the mechanical optimization coefficient with the mechanical optimization threshold: if the mechanical optimization coefficient is less than the mechanical optimization threshold, generate an algorithm optimization signal and send the algorithm optimization signal to the manager's mobile terminal; if the mechanical optimization coefficient is greater than or equal to the mechanical optimization threshold, generate a mechanical optimization signal and send the mechanical optimization signal to the manager's mobile terminal; optimize and analyze the adaptability of the vehicle-mounted control ball, screen the optimization process, and then extract the mirror jitter parameters of the vehicle-mounted control ball during the optimization process for analysis to obtain the mechanical optimization coefficient, so as to make a decision analysis on the video anti-shake optimization direction of the vehicle-mounted control ball through the value of the mechanical optimization coefficient.

[0035] Embodiment 2

[0036] like Figure 2 As shown, a video anti-shake analysis method for a vehicle-mounted control ball includes the following steps:

[0037] Step 1: Perform video jitter test analysis on the vehicle-mounted control ball: generate several simulated test environments, set the driving speed of the test vehicle and the reference vehicle to M1 kilometers per hour, and then perform jitter tests on the test vehicle and the reference vehicle in the simulated test environment to obtain several test processes;

[0038] Step 2: Perform jitter analysis on the test process: During the test process, the vehicle-mounted control ball is used to record the video and decompose the obtained video into test images frame by frame. The offset mean value PJ and the offset protrusion value PT of the test process are obtained through the offset coefficient of the test image, and the jitter coefficient DD of the test process is obtained by numerical calculation;

[0039] Step 3: Evaluate and analyze the video jitter state of the vehicle-mounted control ball and obtain the jitter performance value and jitter stability value of the vehicle-mounted control ball. Determine whether the video jitter state of the vehicle-mounted control ball meets the requirements based on the jitter performance value and the jitter stability value.

[0040] Step 4: Optimize and analyze the adaptability of the vehicle-mounted control ball: mark the test process in which the jitter coefficient DD is not less than the jitter performance threshold as the optimization process, obtain the mechanical optimization coefficient of the optimization process, generate an algorithm optimization signal or a mechanical optimization signal through the mechanical optimization coefficient and send it to the mobile terminal of the manager.

[0041] A video anti-shake analysis system for a vehicle-mounted control ball generates several simulated test environments when working, sets the driving speeds of a test vehicle and a reference vehicle to M1 kilometers per hour, and then performs a jitter test on the test vehicle and the reference vehicle in the simulated test environment to obtain several test processes; during the test process, the vehicle-mounted control ball is used to record the video and the obtained video is decomposed into test images frame by frame, and the offset mean value PJ and the offset protrusion value PT of the test process are obtained through the offset coefficient of the test image, and the jitter coefficient DD of the test process is obtained by numerical calculation; the video jitter state of the vehicle-mounted control ball is evaluated and analyzed to obtain the jitter performance value and jitter stability value of the vehicle-mounted control ball, and whether the video jitter state of the vehicle-mounted control ball meets the requirements is determined by the jitter performance value and the jitter stability value; the test process whose jitter coefficient DD is not less than the jitter performance threshold is marked as an optimization process, and the mechanical optimization coefficient of the optimization process is obtained, and an algorithm optimization signal or a mechanical optimization signal is generated by the mechanical optimization coefficient and sent to a mobile phone terminal of a manager.

[0042] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0043] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula DD = k1*PJ+k2*PT; technicians in this field collect multiple groups of sample data and set corresponding jitter coefficients for each group of sample data; substitute the set jitter coefficients and the collected sample data into the formula, any two formulas constitute a binary linear equation group, the calculated coefficients are screened and averaged, and the values ​​of k1 and k2 are obtained as 3.27 and 2.02 respectively;

[0044] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the initial setting of the corresponding jitter coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value, such as the jitter coefficient is proportional to the value of the offset mean.

[0045] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0046] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A video anti-shake analysis system for vehicle-mounted control ball, characterized in that: It includes a test simulation module, a jitter analysis module, a jitter evaluation module and an adaptive optimization module, wherein the test simulation module, the jitter analysis module, the jitter evaluation module and the adaptive optimization module are sequentially communicatively connected; The test simulation module is used to perform video jitter test analysis on the vehicle-mounted control ball: generate several simulated test environments, set the driving speed of the test vehicle and the reference vehicle to M1 kilometers per hour, and then perform jitter tests on the test vehicle and the reference vehicle in the simulated test environment to obtain several test processes; The jitter analysis module is used to perform jitter analysis on the test process: during the test process, the video is recorded by the vehicle-mounted control ball and the obtained video is decomposed into test images frame by frame, and the position information of the reference vehicle in the test image is extracted; The position information of the reference vehicle in the test image is compared with the position information of the reference vehicle in the previous test image to obtain the offset coefficient of the test image, and then the offset coefficients of all test images are numerically calculated to obtain the jitter coefficient DD of the test process, and the jitter coefficient DD of all test processes is sent to the jitter evaluation module; The jitter evaluation module is used to evaluate and analyze the video jitter state of the vehicle-mounted control ball and obtain the jitter performance value and jitter stability value of the vehicle-mounted control ball, and determine whether the video jitter state of the vehicle-mounted control ball meets the requirements through the jitter performance value and the jitter stability value; The adaptation optimization module is used to optimize the adaptability of the vehicle-mounted control ball; The process of obtaining the jitter performance value and jitter stability value of the vehicle-mounted control ball includes: summing up and averaging the jitter coefficients DD of all test processes to obtain the jitter performance value of the vehicle-mounted control ball, and performing variance calculation on the jitter coefficients DD of all test processes to obtain the jitter stability value of the vehicle-mounted control ball; The specific process of determining whether the video jitter state of the vehicle-mounted control ball meets the requirements includes: comparing the jitter performance value and the jitter stability value of the vehicle-mounted control ball with the preset jitter performance threshold and the jitter stability threshold respectively: if the jitter performance value is less than the jitter performance threshold and the jitter stability value is less than the jitter stability threshold, then it is determined that the video jitter state of the vehicle-mounted control ball meets the requirements; if the jitter performance value is greater than or equal to the jitter performance threshold, then it is determined that the video jitter state of the vehicle-mounted control ball does not meet the requirements, a performance abnormality signal is generated and the performance abnormality signal is sent to the mobile phone terminal of the administrator; if the jitter performance value is less than the jitter performance threshold and the jitter stability value is greater than or equal to the jitter stability threshold, then it is determined that the anti-shake adaptability of the vehicle-mounted control ball does not meet the requirements, an adaptation optimization signal is generated and the adaptation optimization signal is sent to the adaptation optimization module; The specific process of the adaptive optimization module optimizing and analyzing the adaptability of the vehicle-mounted control ball includes: marking the test process in which the jitter coefficient DD is not less than the jitter performance threshold as the optimization process, dividing the optimization process into several optimization periods, obtaining the maximum jitter amplitude and the maximum jitter frequency of the vehicle-mounted control ball mirror in the optimization period and marking them as the jitter amplitude value DF and the jitter frequency value DP respectively, and obtaining the mechanical jitter value JD of the optimization period by numerically calculating the jitter amplitude value DF and the jitter frequency value DP; summing and averaging the mechanical jitter values ​​JD of all optimization periods to obtain the mechanical optimization coefficient of the optimization process, and comparing the mechanical optimization coefficient with the mechanical optimization threshold: if the mechanical optimization coefficient is less than the mechanical optimization threshold, then generating an algorithm optimization signal and sending the algorithm optimization signal to the mobile phone terminal of the manager; if the mechanical optimization coefficient is greater than or equal to the mechanical optimization threshold, then generating a mechanical optimization signal and sending the mechanical optimization signal to the mobile phone terminal of the manager; The calculation formula of the mechanical jitter value JD during the optimization period is: JD=u1×DF+u2×DP, where u1 and u2 are both proportional coefficients, and u1>u2>1.

2. The video anti-shake analysis system for vehicle-mounted control ball according to claim 1 is characterized in that: The simulation test environment includes: setting up L1 speed bumps on the test road, with the height of each speed bump and the distance interval between adjacent speed bumps randomly set, installing the on-board control ball on the test vehicle, and then setting a reference vehicle in front of the test vehicle, with the reference vehicle driving in the same direction as the test vehicle.

3. The video anti-shake analysis system for vehicle-mounted control ball according to claim 2 is characterized in that: The position information extraction process includes: setting a number of reference points on the reference vehicle, extracting the coordinates of the reference points of the reference vehicle in the test image, and then forming the position information from the coordinates of all the reference points.

4. The video anti-shake analysis system for vehicle-mounted control ball according to claim 3 is characterized in that: The process of obtaining the offset coefficient of the test image includes: marking the absolute value of the difference in the horizontal coordinates of the same reference point in the two test images as the horizontal offset value, marking the absolute value of the difference in the vertical coordinates of the same reference point in the two test images as the vertical offset value, marking the sum of the horizontal offset value and the vertical offset value as the overall offset value of the reference point, and summing and averaging the overall offset values ​​of all reference points to obtain the offset coefficient of the test image.

5. The video anti-shake analysis system for vehicle-mounted control ball according to claim 4 is characterized in that: The process of obtaining the jitter coefficient DD includes: summing up the offset coefficients of all test images and taking the average value to obtain the offset mean PJ of the test process, marking the maximum value of the offset coefficient in all test images as the offset prominent value PT of the test process, and numerically calculating the offset mean PJ and the offset prominent value PT to obtain the jitter coefficient DD of the test process.

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