Evidence obtaining method and law enforcement recorder

Abstract

The invention relates to an evidence obtaining method and a law enforcement recorder, and the method comprises the steps: obtaining and storing an image in a visual field range, and synchronously obtaining working parameters of an anti-shake unit, the working parameters comprising a displacement amount and a displacement direction; classifying the obtained images by using the working parameters, wherein the classification comprises clear images and unclear images; determining working parameters corresponding to the unclear image, and determining an adjustment direction according to a displacement direction in the working parameters; and determining a vibration degree value of the unclear image in the adjusting direction, selecting a definition adjusting mode according to the vibration degree value, selecting a merging processing mode to adjust the definition of the image when the vibration degree value is zero, and selecting a deleting processing mode to adjust the definition of the image when the vibration degree value is greater than zero. According to the evidence obtaining method and the law enforcement recorder disclosed by the invention, the image is processed by combining an algorithm on the basis of mechanical anti-shake, and the processing mode combines the advantages of two anti-shake modes, so that the image obtained in the evidence obtaining process is clearer.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method for collecting evidence and a law enforcement recorder. Background Art

[0002] The law enforcement recorder is a kind of evidence collection technology equipment that integrates real-time video and audio recording, photography and video recording. It integrates the functions of video recording, photography, intercom, positioning and storage. At the same time, it can digitally record the dynamic and static on-site conditions during law enforcement through wireless real-time video transmission. The images stored in the law enforcement recorder serve as important supporting documents in the subsequent process and need to have a certain clarity, otherwise it is easy to cause dispute areas.

[0003] When shooting images, the most commonly used processing method is anti-shake. The mainstream anti-shake methods are OIS anti-shake and CCD anti-shake. The principle of OIS anti-shake is to add a magnetically suspended lens to the lens group. When the device shakes, the floating lens will be controlled to compensate for the displacement. However, its anti-shake range is relatively limited, and there will be obvious blur at the edge of the picture. The principle of CCD anti-shake is that the lens does not move, but the photoelectric sensor is installed on a bracket that can float freely. According to the direction and amplitude of the body's shake, the posture is adjusted for compensation. This structure can avoid the influence of the OIS structure on the imaging effect, and can achieve up to 5-axis anti-shake (OIS only 2 axes). However, due to its high structural precision and as the lens is pulled from the wide-angle end to the telephoto end, its anti-shake effect will become worse and worse.

[0004] Another way is to use algorithms to implement it. The advantage of this method is that it gets rid of hardware limitations, but the scenarios it can cope with are limited. This is mainly because the influencing conditions of multiple scenarios are complex, and the algorithm has certain difficulties in judgment and specific implementation. Summary of the invention

[0005] The present application provides a method for collecting evidence and a law enforcement recorder, which processes images based on mechanical anti-shake and an algorithm. This processing method combines the advantages of two anti-shake methods and can make the images obtained in the evidence collection process clearer.

[0006] The above-mentioned purpose of the present application is achieved through the following technical solutions:

[0007] In a first aspect, the present application provides a method for obtaining evidence, comprising:

[0008] Acquire and store images within the field of view, and simultaneously acquire working parameters of the anti-shake unit, the working parameters including displacement amount and displacement direction;

[0009] Using the working parameters to classify the acquired images, the classification includes clear images and unclear images;

[0010] Determine the working parameters corresponding to the unclear image and determine the adjustment direction according to the displacement direction in the working parameters;

[0011] Determine the vibration value of the unclear image in the adjustment direction;

[0012] Select the clarity adjustment method according to the vibration value. When the vibration value is zero, select the merge processing method to adjust the image clarity. When the vibration value is greater than zero, select the delete processing method to adjust the image clarity.

[0013] In a possible implementation manner of the first aspect, adjusting the clarity of the image by using the merging processing manner includes:

[0014] An image group is generated in a time series, where the image group includes a clear image and multiple unclear images;

[0015] Performing synthesis processing on the images in the image group to obtain a synthesized image;

[0016] Moving the unsharp image included in the composite image in the adjustment direction so that the unsharp image overlaps with the clear image;

[0017] Adjust the clarity of the unclear image based on the overlap result.

[0018] In a possible implementation manner of the first aspect, adjusting the clarity of the unclear image according to the overlap result includes:

[0019] Selecting an unsharp image from among the multiple unsharp images included in the image group as the image to be adjusted, wherein there is at least one unsharp image between the image to be adjusted and the clear image included in the image group;

[0020] Superimposing the unclear image included in the image group onto the image to be adjusted to obtain a superimposed adjusted image;

[0021] Establishing an analysis line on the overlay adjustment image and screening the analysis line using the overlay quantity, the peak number of the analysis line is equal to the overlay quantity;

[0022] Using the adjacent peak distances on the screened analysis line, the unsharp image belonging to the superimposed adjustment image is moved so that the unsharp image coincides with the clear image;

[0023] Adjusting the corresponding position on the unclear image according to the overlapped area, the adjustment includes weakening both sides of the overlapped area on the unclear image;

[0024] The adjacent peak distances are obtained by averaging the adjacent peak distances on multiple analysis lines.

[0025] In a possible implementation manner of the first aspect, when a non-overlapping area appears on the superimposed adjustment image, the adjacent peak distance is changed and the unsharp image belonging to the superimposed adjustment image is moved again, and at this time only the non-overlapping area on the unsharp image belonging to the superimposed adjustment image is moved.

[0026] In a possible implementation manner of the first aspect, when the clarity of the non-overlapping area after the movement does not meet the requirement, the method further includes:

[0027] Establishing an analysis line in a direction parallel to the adjustment direction and determining a moving reference point and a moving reference distance corresponding to the moving reference point using the analysis line;

[0028] Determine the rotation angle with reference to the moving reference distance;

[0029] The non-overlapping areas on the unclear image belonging to the superimposed adjustment image are moved using the working parameters and the rotation angle until the clarity of the non-overlapping areas after the movement meets the requirements.

[0030] In a possible implementation manner of the first aspect, adjusting the clarity of the image by using the deletion processing manner includes:

[0031] Determine the moving direction according to the working parameters;

[0032] A deletion processing reference line is established on the adjusted image, and the deletion processing reference line is parallel to the moving direction;

[0033] Use the pixels on the deletion processing reference line to establish a deletion processing reference difference value series;

[0034] The peak points of the reference difference value series are obtained by analysis and deletion, and the number of the peak points is at least two;

[0035] Calculate the distance between adjacent peak points to obtain the deletion reference distance;

[0036] Use the deletion reference distance to delete or move the redundant pixels on the image.

[0037] In a possible implementation manner of the first aspect, the method further includes:

[0038] Decomposing the adjusted image into a plurality of sub-adjusted images using a removal reference distance;

[0039] Selecting a plurality of influence points on each sub-adjustment image, wherein positions of corresponding influence points on each sub-adjustment image are the same;

[0040] Calculate the pixel value of the influencing point and obtain the pixel value result;

[0041] The sub-adjusted images are deleted using the pixel value results, and only the sub-adjusted image with the largest pixel value result is retained.

[0042] In a second aspect, the present application provides a forensics device, comprising:

[0043] An image acquisition unit, used to acquire and store images within a field of view, and synchronously acquire working parameters of the anti-shake unit, the working parameters including displacement amount and displacement direction;

[0044] An image classification unit, used to classify the acquired images using the working parameters, the classification including clear images and unclear images;

[0045] A first parameter determination unit, used to determine the working parameters corresponding to the unclear image and determine the adjustment direction according to the displacement direction in the working parameters;

[0046] A second parameter determination unit, used to determine a vibration value of an unclear image in an adjustment direction;

[0047] The clarity adjustment unit is used to select a clarity adjustment method according to the vibration value. When the vibration value is zero, a merging processing method is selected to adjust the clarity of the image. When the vibration value is greater than zero, a deleting processing method is selected to adjust the clarity of the image.

[0048] In a third aspect, the present application provides a law enforcement recorder, the law enforcement recorder comprising:

[0049] one or more memories for storing instructions; and

[0050] One or more processors, used to call and run the instructions from the memory to execute the method as described in the first aspect and any possible implementation of the first aspect.

[0051] In a fourth aspect, the present application provides a computer-readable storage medium, the computer-readable storage medium comprising:

[0052] Program, when the program is executed by a processor, the method described in the first aspect and any possible implementation of the first aspect is executed.

[0053] In a fifth aspect, the present application provides a computer program product, comprising program instructions. When the program instructions are executed by a computing device, the method described in the first aspect and any possible implementation of the first aspect is executed.

[0054] In a sixth aspect, the present application provides a chip system, which includes a processor for implementing the functions involved in the above aspects, for example, generating, receiving, sending, or processing the data and / or information involved in the above methods.

[0055] The chip system may be composed of chips, or may include chips and other discrete devices.

[0056] In a possible design, the chip system also includes a memory, which is used to store necessary program instructions and data. The processor and the memory can be decoupled and respectively set on different devices, connected by wired or wireless means, or the processor and the memory can also be coupled on the same device. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a schematic flowchart of the steps of a forensics method provided by this application.

[0058] Figure 2 This is a schematic diagram provided by the present application for classifying acquired images using working parameters.

[0059] Figure 3 This is a schematic diagram of generating an image group in a time series provided by the present application.

[0060] Figure 4 It is a schematic diagram of an interval processing method provided by this application.

[0061] Figure 5 This is a schematic diagram of determining a rotation angle provided by the present application.

[0062] Figure 6 This is a schematic diagram of deleting a reference distance provided by the present application. DETAILED DESCRIPTION

[0063] The technical solution in this application is further described in detail below in conjunction with the accompanying drawings.

[0064] This application discloses a method for obtaining evidence, see Figure 1 In some examples, the evidence collection method disclosed in this application includes the following steps:

[0065] S101, acquiring and storing an image within a field of view, and synchronously acquiring working parameters of an anti-shake unit, the working parameters including a displacement amount and a displacement direction;

[0066] S102, using the working parameters to classify the acquired images, the classification including clear images and unclear images;

[0067] S103, determining working parameters corresponding to the unclear image and determining an adjustment direction according to a displacement direction in the working parameters;

[0068] S104, determining a vibration value of the unclear image in the adjustment direction;

[0069] S105, selecting a definition adjustment method according to the vibration value. When the vibration value is zero, selecting a merging processing method to adjust the image definition. When the vibration value is greater than zero, selecting a deleting processing method to adjust the image definition.

[0070] First of all, it needs to be explained that the evidence collection method disclosed in the present application is applied to law enforcement recorders. The image sensor in the law enforcement recorder has a mechanical anti-shake structure (OIS anti-shake structure or CCD anti-shake structure). When the image taken by the image sensor does not meet the clarity requirements, it will be processed using the evidence collection method disclosed in the present application to obtain a clear image during the evidence collection process.

[0071] Specifically, in step S101, the image sensor in the law enforcement recorder obtains and stores the image within the field of view. The storage location is the memory in the law enforcement recorder. At the same time, the law enforcement recorder will synchronously obtain the working parameters of the anti-shake unit. The working parameters include displacement and displacement direction. The displacement direction refers to the adjustment direction of the anti-shake unit, and the displacement refers to the adjustment amount of the anti-shake unit in the adjustment direction.

[0072] It should be understood that the adjustment amount of the anti-shake unit in the adjustment direction is directly related to the clarity of the image. In a unit time length, the adjustment amount of the anti-shake unit in the adjustment direction and the clarity of the image are negatively correlated. Therefore, in step S102, the acquired images are classified using the working parameters. The classification includes clear images and unclear images, such as Figure 2 shown.

[0073] A fixed reference value is set here. When the working parameter is greater than the fixed reference value, the image clarity needs to be adjusted. When the working parameter is less than the fixed reference value, the image clarity does not need to be adjusted.

[0074] This method is equivalent to the initial classification of the images obtained by the image sensor in the law enforcement recorder. The purpose of classification is to reasonably divide the image processing methods. For fixed reference values, they need to be determined based on the specific parameters and requirements of the law enforcement recorder, and are not restricted here.

[0075] In step S103, the working parameters corresponding to the unclear image are determined and the adjustment direction is determined according to the displacement direction in the working parameters. The working parameters corresponding to the unclear image here refer to the movement amount of the mechanical anti-shake structure.

[0076] For the OIS anti-shake structure, the working parameter refers to the compensation displacement calculated based on the tiny movements detected by the gyroscope in the lens; for the CCD anti-shake structure, the working parameter refers to the compensation displacement calculated based on the tiny movements detected by the sensor on the bracket.

[0077] In step S104, the vibration value of the unclear image is determined in the adjustment direction. The vibration value refers to whether there is a ghost on the unclear image. If there is one ghost, the vibration value is one, if there are two ghosts, the vibration value is two, and so on.

[0078] Here, the vibration value range is generally controlled within the required range (2-4). When the vibration value exceeds the range, it is necessary to first adjust the exposure time to make the vibration value of the unclear image return to the required range.

[0079] It should be noted that when the vibration value range exceeds the allowable range, it means that the relative movement speed of the photo is too fast. At this time, the relative movement speed should be reduced by shortening the exposure time.

[0080] In step S105, a definition adjustment method is selected according to the vibration value. When the vibration value is zero, a merging processing method is selected to adjust the image definition. When the vibration value is greater than zero, a deleting processing method is selected to adjust the image definition.

[0081] The specific method of using the merge processing method to adjust the clarity of the image is:

[0082] S201, generating an image group in a time series, the image group including a clear image and a plurality of unclear images;

[0083] S202, synthesizing the images in the image group to obtain a synthesized image;

[0084] S203, moving the unclear image included in the synthesized image in the adjustment direction so that the unclear image overlaps with the clear image;

[0085] S204: adjusting the clarity of the unclear image according to the overlap result.

[0086] In step 201, an image group is first generated in time series. Figure 3 As shown, the image group includes a clear image and multiple unclear images. The clear image and the unclear images in the image group are continuous in time series. Then, the images in the image group are synthesized to obtain a synthesized image, which is the content in step S202. The synthesis processing method is to merge the images in the same group into one image.

[0087] In step S203, the unsharp image included in the composite image is moved in the adjustment direction so that the unsharp image overlaps with the clear image, and finally in step S204, the clarity of the unsharp image is adjusted according to the overlap result.

[0088] The above method is to use the clear image to adjust the unclear image, because the unclear image at this time is unclear due to the loss of certain information, and the lost information can be obtained by referring to the clear image.

[0089] The specific method of adjusting the clarity of the unclear image according to the overlap result is:

[0090] Selecting an unsharp image from among the multiple unsharp images included in the image group as the image to be adjusted, wherein there is at least one unsharp image between the image to be adjusted and the clear image included in the image group;

[0091] Superimposing the unclear image included in the image group onto the image to be adjusted to obtain a superimposed adjusted image;

[0092] Establishing an analysis line on the overlay adjustment image and screening the analysis line using the overlay quantity, the peak number of the analysis line is equal to the overlay quantity;

[0093] Using the adjacent peak distances on the screened analysis line, the unsharp image belonging to the superimposed adjustment image is moved so that the unsharp image coincides with the clear image;

[0094] Adjusting the corresponding position on the unclear image according to the overlapped area, the adjustment includes weakening both sides of the overlapped area on the unclear image;

[0095] The adjacent peak distances are obtained by averaging the adjacent peak distances on multiple analysis lines.

[0096] In this method, for unclear images, an interval processing method is used, such as Figure 4 As shown, there needs to be at least one unclear image between the image to be adjusted and the clear image included in the image group. For the unclear image that has not been processed, a difference method is used to generate it.

[0097] During adjustment, the unclear image included in the image group is first superimposed on the image to be adjusted to obtain a superimposed adjustment image, and then an analysis line is established on the superimposed adjustment image and the analysis line is screened using the superimposed number, and the peak number of the analysis line is equal to the superimposed number.

[0098] The reason for screening the analysis lines is that the number of peaks of the analysis lines may be less than the number of superpositions. This is because the information loss area on the unclear image is uncertain, so screening is required. The number of peaks of the analysis lines obtained by screening is equal to the number of superpositions.

[0099] The adjacent peak distances are calculated by averaging the adjacent peak distances on multiple analysis lines.

[0100] In some possible implementations, the peak on the analysis line is obtained by using the pixels on the analysis line to establish a difference series or to generate a quadratic difference series based on the difference series, and the peak of the curve corresponding to the difference series or the quadratic difference series is the peak on the analysis line.

[0101] In some possible implementations, grayscale processing is performed on the overlay adjustment image while establishing the analysis line on the overlay adjustment image.

[0102] Then, the unsharp image belonging to the superimposed adjustment image is moved using the adjacent peak distances on the screened analysis lines so that the unsharp image overlaps with the clear image, and then the corresponding position on the unsharp image is adjusted according to the overlapping area. The adjustment includes weakening both sides of the overlapping area on the unsharp image, so that the displayed content on the unsharp image can be clearer.

[0103] In some possible implementations, the way to weaken the two sides of the overlapping area on the unclear image is to define a weakened area and then reduce the values ​​of the pixels in the weakened area by a certain amount. Generally speaking, the width of the weakened area is controlled between 6-8 pixels, and the reduction method is to reduce the values ​​of the pixels by a certain ratio, and the reduction ratio is controlled at 10%-15%.

[0104] In some examples, when a non-overlapping area appears on the superimposed adjustment image, the adjacent peak distance is changed and the unsharp image belonging to the superimposed adjustment image is moved again, and only the non-overlapping area on the unsharp image belonging to the superimposed adjustment image is moved.

[0105] That is, the unclear image is partitioned, and the partitioning method is to optimize each area on the unclear image.

[0106] The reason for using partition processing is that the movement amount of each area is different. At this time, it is also necessary to consider that the distance distribution between peak points is uneven and it is impossible to make the unclear image and the clear image completely overlap. Therefore, a certain amount of non-overlapping areas are allowed, and the ratio of non-overlapping areas to overlapping areas is controlled at 3%-5%.

[0107] When the clarity of the non-overlapping area after moving does not meet the requirements, use the following method to handle it:

[0108] S301, establishing an analysis line in a direction parallel to the adjustment direction and using the analysis line to determine a moving reference point and a moving reference distance corresponding to the moving reference point;

[0109] S302, determining a rotation angle with reference to a moving reference distance;

[0110] S303, using the working parameters and the rotation angle to move the non-overlapping area on the unclear image belonging to the superimposed adjustment image until the clarity of the non-overlapping area after the movement meets the requirement.

[0111] The contents in step S301 to step S303 are mainly to take into account that the non-overlapping area may have rotated, and in this case, it is impossible to make the non-overlapping area meet the definition requirements by moving. In order to solve this problem, in step S301 to step S303, an analysis line is established in the direction parallel to the adjustment direction and the analysis line is used to determine the moving reference point and the moving reference distance corresponding to the moving reference point. Figure 5 As shown, the rotation angle is then determined with reference to the moving reference distance. At this time, the adjustment direction in the working parameters is not parallel to the adjustment direction, and there is an angle between the two.

[0112] At this time, the working parameters and the rotation angle can be used to move the non-overlapping area on the unclear image belonging to the superimposed adjustment image until the clarity of the non-overlapping area after the movement meets the requirements.

[0113] Of course, at this time, some parts may move too fast. In this case, we can use the method of adjusting the exposure time to improve it. If the above method cannot meet the requirements, use the following method to deal with it:

[0114] An analysis line is established in the same direction as the adjustment direction, and then the pixels on the analysis line are used to generate a difference series or a quadratic difference series of the difference series. The difference series or the quadratic difference series is then used to determine the peak area. The width of the peak area is generally controlled at 3-5 pixels.

[0115] A rectangular area is divided on the peak area, the center of the rectangular area is determined and the mean value of the pixels in the rectangular area is used as the pixel value of the center point. These centers are then connected together in sequence as a more obvious outline, and the values ​​of other pixel points in the rectangular area are weakened by 10%-15%.

[0116] In some examples, the specific ways to adjust the clarity of an image using the removal process are:

[0117] S401, determining a moving direction according to working parameters;

[0118] S402, establishing a deletion processing reference line on the adjusted image, wherein the deletion processing reference line is parallel to the moving direction;

[0119] S403, using the pixel points on the deletion processing reference line to establish a deletion processing reference difference value series;

[0120] S404, analyzing and obtaining the peak points of the reference difference value series for deletion processing, where the number of the peak points is at least two;

[0121] S405, calculating the distance between adjacent peak points to obtain a deletion reference distance;

[0122] S406: Use the deletion reference distance to delete or move the redundant pixels on the adjustment image.

[0123] The content in step S401 to step S406 first determines the moving direction according to the working parameters, then establishes a deletion processing reference line on the adjusted image, the deletion processing reference line needs to be parallel to the moving direction, and then uses the pixel points on the deletion processing reference line to establish a deletion processing reference difference series.

[0124] Then determine the peak points of the reference difference series for deletion processing. The number of peak points is at least two, because of the overlapping effect of the image. Finally, calculate the distance between adjacent peak points to obtain the deletion reference distance. Figure 6 As shown, then use the delete reference distance to delete or move the redundant pixels on the image.

[0125] The method to delete the redundant pixels on the adjusted image is as follows:

[0126] Decomposing the adjusted image into a plurality of sub-adjusted images using a removal reference distance;

[0127] Selecting a plurality of influence points on each sub-adjustment image, wherein positions of corresponding influence points on each sub-adjustment image are the same;

[0128] Calculate the pixel value of the influencing point and obtain the pixel value result;

[0129] The sub-adjusted images are deleted using the pixel value results, and only the sub-adjusted image with the largest pixel value result is retained.

[0130] Delete the remaining blank pixels and use the adjacent pixels on both sides for repair. The repair method refers to the color and value. The color uses the same color (the colors under the adjacent pixels on both sides are the same) or the average color (the colors under the adjacent pixels on both sides are different). The value is obtained using the mean method.

[0131] The method of moving the redundant pixels on the adjusted image is to move the decomposed sub-adjusted images according to the deletion reference distance, so that the sub-adjusted images can overlap as much as possible.

[0132] The present application also provides a forensics device, comprising:

[0133] An image acquisition unit, used to acquire and store images within a field of view, and synchronously acquire working parameters of the anti-shake unit, the working parameters including displacement amount and displacement direction;

[0134] An image classification unit, used to classify the acquired images using the working parameters, the classification including clear images and unclear images;

[0135] A first parameter determination unit, used to determine the working parameters corresponding to the unclear image and determine the adjustment direction according to the displacement direction in the working parameters;

[0136] A second parameter determination unit, used to determine a vibration value of an unclear image in an adjustment direction;

[0137] The clarity adjustment unit is used to select a clarity adjustment method according to the vibration value. When the vibration value is zero, a merging processing method is selected to adjust the clarity of the image. When the vibration value is greater than zero, a deleting processing method is selected to adjust the clarity of the image.

[0138] Furthermore, it also includes:

[0139] An image group generating unit, used for generating an image group in a time series, wherein the image group includes a clear image and a plurality of unclear images;

[0140] A synthesis processing unit, used for synthesizing the images in the image group to obtain a synthesized image;

[0141] A first moving unit is used to move the unclear image included in the composite image in an adjustment direction so that the unclear image overlaps with the clear image;

[0142] The clarity adjustment unit is used to adjust the clarity of the unclear image according to the overlap result.

[0143] Furthermore, it also includes:

[0144] An image selection unit, configured to select an unsharp image from among a plurality of unsharp images included in the image group as an image to be adjusted, wherein there is at least one unsharp image between the image to be adjusted and the clear image included in the image group;

[0145] A superimposition processing unit, used for superimposing the unclear image included in the image group onto the image to be adjusted to obtain a superimposed adjusted image;

[0146] an analysis line processing unit, for establishing analysis lines on the overlay adjustment image and screening the analysis lines using the overlay quantity, wherein the peak quantity of the analysis line is equal to the overlay quantity;

[0147] A second moving unit is used to move the unsharp image belonging to the superimposed adjustment image using the adjacent peak distances on the screened analysis line so that the unsharp image overlaps with the clear image;

[0148] A corresponding position adjustment unit, used to adjust the corresponding position on the unclear image according to the overlapped area, wherein the adjustment includes weakening both sides of the overlapped area on the unclear image;

[0149] The adjacent peak distances are obtained by averaging the adjacent peak distances on multiple analysis lines.

[0150] Further, when a non-overlapping area appears on the superimposed adjustment image, the adjacent peak distance is changed and the unclear image belonging to the superimposed adjustment image is moved again, and at this time, only the non-overlapping area on the unclear image belonging to the superimposed adjustment image is moved.

[0151] Furthermore, it also includes:

[0152] a first processing unit, configured to establish an analysis line in a direction parallel to the adjustment direction and determine a moving reference point and a moving reference distance corresponding to the moving reference point using the analysis line;

[0153] A rotation angle determination unit, used to determine the rotation angle with reference to the moving reference distance;

[0154] The second processing unit is used to move the non-overlapping area on the unclear image belonging to the superimposed adjustment image using the working parameters and the rotation angle until the clarity of the non-overlapping area after the movement meets the requirement.

[0155] Furthermore, it also includes:

[0156] A rotation direction determination unit, used to determine the moving direction according to the working parameters;

[0157] A third processing unit is used to establish a deletion processing reference line on the adjusted image, where the deletion processing reference line is parallel to the moving direction;

[0158] A fourth processing unit, configured to establish a deletion processing reference difference value series using pixel points on the deletion processing reference line;

[0159] An analysis and processing unit, used for analyzing and obtaining peak points of a deletion processing reference difference value series, wherein the number of peak points is at least two;

[0160] A first calculation processing unit, used for calculating the distance between adjacent peak points to obtain a deletion reference distance;

[0161] The fifth processing unit is used to delete or move redundant pixels on the image using a deletion reference distance.

[0162] Furthermore, it also includes:

[0163] a decomposition unit, configured to decompose the adjusted image into a plurality of sub-adjusted images using a deletion reference distance;

[0164] An influence point selection unit, used for selecting a plurality of influence points on each sub-adjustment image, wherein the positions of the corresponding influence points on each sub-adjustment image are the same;

[0165] A second calculation processing unit is used to calculate the pixel value of the influence point to obtain a pixel value result;

[0166] The deletion processing unit is used to delete the sub-adjusted image using the pixel value result, and only retain the sub-adjusted image with the largest pixel value result.

[0167] In one example, the unit in any of the above devices can be one or more integrated circuits configured to implement the above methods, such as: one or more application specific integrated circuits (ASICs), or, one or more digital signal processors (DSPs), or, one or more field programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms.

[0168] For another example, when the units in the device can be implemented in the form of a processing element scheduling program, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processor that can call a program. For another example, these units can be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0169] Various objects such as various messages / information / equipment / network elements / systems / devices / actions / operations / processes / concepts that may appear in this application are named. It can be understood that these specific names do not constitute a limitation on the relevant objects. The names assigned may change with factors such as scenarios, contexts or usage habits. The understanding of the technical meaning of the technical terms in this application should be mainly determined from the functions and technical effects embodied / executed in the technical scheme.

[0170] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0171] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0172] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0173] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0174] It should also be understood that in various embodiments of the present application, the first, second, etc. are only used to indicate that multiple objects are different. For example, the first time window and the second time window are only used to indicate different time windows. They should not have any impact on the time window itself, and the first, second, etc. mentioned above should not impose any limitations on the embodiments of the present application.

[0175] It should also be understood that in the various embodiments of the present application, unless otherwise specified or there is a logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced to each other, and the technical features in different embodiments can be combined to form new embodiments according to their internal logical relationships.

[0176] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. 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 computer-readable storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned computer-readable storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0177] The present application also provides a law enforcement recorder, the law enforcement recorder comprising:

[0178] one or more memories for storing instructions; and

[0179] One or more processors are used to call and run the instructions from the memory to execute the method as described above.

[0180] The present application also provides a computer program product, which includes instructions. When the instructions are executed, the terminal device and the network device perform operations of the terminal device and the network device corresponding to the above method.

[0181] The present application also provides a chip system, which includes a processor for implementing the functions involved in the above content, such as generating, receiving, sending, or processing the data and / or information involved in the above method.

[0182] The chip system may be composed of chips, or may include chips and other discrete devices.

[0183] The processor mentioned in any of the above places can be a CPU, a microprocessor, an ASIC, or one or more integrated circuits for executing programs for controlling the above-mentioned feedback information transmission method.

[0184] In a possible design, the chip system also includes a memory, which is used to store necessary program instructions and data. The processor and the memory can be decoupled and respectively set on different devices, connected by wire or wireless means to support the chip system to implement various functions in the above embodiments. Alternatively, the processor and the memory can also be coupled on the same device.

[0185] Optionally, the computer instructions are stored in a memory.

[0186] Optionally, the memory is a storage unit within the chip, such as a register, a cache, etc. The memory can also be a storage unit within the terminal located outside the chip, such as a ROM or other types of static storage devices that can store static information and instructions, RAM, etc.

[0187] It can be understood that the memory in the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories.

[0188] The non-volatile memory may be a ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), or a flash memory.

[0189] The volatile memory may be a RAM, which is used as an external cache. There are many different types of RAM, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct memory bus random access memory.

[0190] The embodiments of this specific implementation method are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Therefore, all equivalent changes made based on the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for obtaining evidence, characterized in that: include: Acquire and store images within the field of view, and simultaneously acquire working parameters of the anti-shake unit, the working parameters including displacement amount and displacement direction; Using the working parameters to classify the acquired images, the classification includes clear images and unclear images; Determine the working parameters corresponding to the unclear image and determine the adjustment direction according to the displacement direction in the working parameters; Determine the vibration value of the unclear image in the adjustment direction; Select the clarity adjustment method according to the vibration value. When the vibration value is zero, select the merge processing method to adjust the image clarity. When the vibration value is greater than zero, select the delete processing method to adjust the image clarity.

2. The evidence collection method according to claim 1, characterized in that: The merge processing methods used to adjust the clarity of the image include: An image group is generated in a time series, where the image group includes a clear image and multiple unclear images; Performing synthesis processing on the images in the image group to obtain a synthesized image; Moving the unsharp image included in the composite image in the adjustment direction so that the unsharp image overlaps with the clear image; Adjust the clarity of the unclear image based on the overlap result.

3. The evidence collection method according to claim 2, characterized in that: Adjusting the clarity of the unclear image based on the overlap result includes: Selecting an unsharp image from among the multiple unsharp images included in the image group as the image to be adjusted, wherein there is at least one unsharp image between the image to be adjusted and the clear image included in the image group; Superimposing the unclear image included in the image group onto the image to be adjusted to obtain a superimposed adjusted image; Establishing an analysis line on the overlay adjustment image and screening the analysis line using the overlay quantity, the peak number of the analysis line is equal to the overlay quantity; Using the adjacent peak distances on the screened analysis line, the unsharp image belonging to the superimposed adjustment image is moved so that the unsharp image coincides with the clear image; Adjusting the corresponding position on the unclear image according to the overlapped area, the adjustment includes weakening both sides of the overlapped area on the unclear image; The adjacent peak distances are obtained by averaging the adjacent peak distances on multiple analysis lines.

4. The evidence collection method according to claim 3, characterized in that: When a non-overlapping area appears on the superimposed adjustment image, the adjacent peak distance is changed and the unclear image belonging to the superimposed adjustment image is moved again, and at this time, only the non-overlapping area on the unclear image belonging to the superimposed adjustment image is moved.

5. The evidence collection method according to claim 3, characterized in that: When the clarity of the non-overlapping area after movement does not meet the requirements, it also includes: Establishing an analysis line in a direction parallel to the adjustment direction and determining a moving reference point and a moving reference distance corresponding to the moving reference point using the analysis line; Determine the rotation angle with reference to the moving reference distance; The non-overlapping areas on the unclear image belonging to the superimposed adjustment image are moved using the working parameters and the rotation angle until the clarity of the non-overlapping areas after the movement meets the requirements.

6. The evidence collection method according to claim 1, characterized in that: Adjusting the clarity of an image using the removal process includes: Determine the moving direction according to the working parameters; A deletion processing reference line is established on the adjusted image, and the deletion processing reference line is parallel to the moving direction; Use the pixel points on the deletion processing reference line to establish a deletion processing reference difference value series; The peak points of the reference difference value series are obtained by analysis and deletion, and the number of the peak points is at least two; Calculate the distance between adjacent peak points to obtain the deletion reference distance; Use the deletion reference distance to delete or move the redundant pixels on the image.

7. The evidence collection method according to claim 6, characterized in that: When you select the deletion reference distance to delete redundant pixels, it also includes: Decomposing the adjusted image into a plurality of sub-adjusted images using a removal reference distance; Selecting a plurality of influence points on each sub-adjustment image, wherein positions of corresponding influence points on each sub-adjustment image are the same; Calculate the pixel value of the influencing point and obtain the pixel value result; The sub-adjusted images are deleted using the pixel value results, and only the sub-adjusted image with the largest pixel value result is retained.

8. A forensics device, characterized in that: include: An image acquisition unit, used to acquire and store images within a field of view, and synchronously acquire working parameters of the anti-shake unit, the working parameters including displacement amount and displacement direction; An image classification unit, used to classify the acquired images using the working parameters, the classification including clear images and unclear images; A first parameter determination unit, used to determine the working parameters corresponding to the unclear image and determine the adjustment direction according to the displacement direction in the working parameters; A second parameter determination unit, used to determine a vibration value of an unclear image in an adjustment direction; The clarity adjustment unit is used to select a clarity adjustment method according to the vibration value. When the vibration value is zero, a merging processing method is selected to adjust the clarity of the image. When the vibration value is greater than zero, a deleting processing method is selected to adjust the clarity of the image.

9. A law enforcement recorder, characterized in that: The law enforcement recorder includes: one or more memories for storing instructions; and One or more processors, configured to call and execute the instructions from the memory to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer readable storage medium comprises: The program, when the program is executed by a processor, the method according to any one of claims 1 to 7 is executed.

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