High-frequency electronic camera system

Abstract

The invention discloses a high-frequency electronic camera system, and the high-frequency electronic camera system provided by the embodiment of the invention is applied to a scene in which an industrial camera is used as a collector for color sorter screening. A camera used for shooting a top view of a material is defined as a main shooting camera, a camera used for shooting a side view of the material is defined as a high-angle shooting camera, a camera used for shooting a front view of the material is defined as a front shooting camera, the corresponding material is a shooting target, and an area before entering a shooting area is defined as a travel area; defining an area passing through the shooting area as an additional recording area; wherein the area corresponding to the main shooting camera is a shooting area, and the area corresponding to the front shooting camera is a travel area; an area corresponding to the high-angle shooting camera is an additional recording area; when materials pass through the travel area, the shooting area and the additional recording area through the conveying device, images of the materials can be collected by the main shooting camera, the front shooting camera and the high-angle shooting camera correspondingly.

Description

Technical Field

[0001] The invention belongs to the field of image processing, and in particular relates to a high-frequency electronic camera system. Background Art

[0002] High-speed cameras have been used in research for many years, some of which are quite practical, such as recording car crash simulations. Only recently have these research tools been adopted by the entertainment industry. Portable models are used for commercial television and film, capturing bullet impacts on "CSI," explosions on "MythBusters," and the flying animal stunts in Disney's "Earth."

[0003] On television, video is played at 30 frames per second, which is comfortable for the human eye. Most television shows and home movies are recorded at the same rate. However, high-speed cameras can record at 325,000 frames per second (one second equals three hours of playback). When the camera operates this fast, powerful lighting is required, and all crew members must use oven mitts to operate the focusing lens.

[0004] Kerney previously rented and sold high-speed cameras to production companies (for slow-motion footage) and manufacturers (for troubleshooting production lines). He explained that high-speed cameras with megapixel resolution, high color sensitivity, and high light sensitivity have been available for a long time. However, until then, these cameras were used to produce black-and-white footage. Sports programming companies like CBS were among the first to use high-speed cameras on network television, with their Emmy-winning program "SwingVision," which documented professional golfers' golf swings.

[0005] High-speed cameras are constantly evolving. The "Time Warp" filming incorporated a small, battery-powered camera to capture footage from the skydive. Kerney also wants to use ultraviolet light, infrared light, and time-lapse photography to warp time.

[0006] High-speed cameras can quickly and repeatedly sample high-speed targets in a short period of time. When projected at a normal speed, the recorded target's changes appear clearly and slowly before our eyes. High-speed camera technology offers outstanding advantages such as real-time target capture, rapid image recording, instant playback, and intuitive and clear images.

[0007] When a high-speed moving target is illuminated by natural light or artificial auxiliary lighting, it generates reflected light, or the target itself emits light. A portion of this light passes through the imaging lens of a high-speed imaging system. After being imaged by the lens, it falls onto the image-sensing surface of the optoelectronic imaging device. Controlled by the driver circuit, the optoelectronic device rapidly responds to the target image on the image-sensing surface. Based on the distribution of the target image's light energy on the image-sensing surface, it generates charge packets of corresponding size at each sampling point, or pixel, completing the photoelectric conversion of the image. Each charge packet carrying the image information is rapidly transferred to a readout register. After signal processing, the readout signal is transmitted to a computer, which reads, displays, interprets, and outputs the image. Therefore, a complete high-speed imaging system consists of several components: optical imaging, optoelectronic imaging, signal transmission, control, and image storage and processing.

[0008] However, existing high-speed cameras still experience blurring and insufficient resolution when shooting at too high a speed. Summary of the Invention

[0009] The object of the present invention is to provide a high-frequency electronic camera system for solving the problem that existing high-speed cameras still have blurring and insufficient resolution when shooting at too high a speed.

[0010] The purpose of the present invention can be achieved through the following technical solutions:

[0011] A high-frequency electronic camera system comprising:

[0012] The acquisition module is used to acquire the material image information transmitted by the color sorter; the material image information includes: main acquisition information, supplementary acquisition information and trip acquisition information;

[0013] A splicing module is used to randomly retrieve any two types of information from the main collected information, the supplementary collected information, or the itinerary collected information and splice them to form an identification photo;

[0014] A screening module is used to screen the identification photos;

[0015] If the screening conditions are met, the identification photo will be sent to the recognition module for identification;

[0016] If the screening conditions are not met, the identification photo is supplemented with details to obtain a supplementary identification photo, and the supplementary identification photo is sent to the recognition module for recognition;

[0017] The recognition module is used to recognize the spliced ​​identification photos or supplementary identification photos.

[0018] Furthermore, the acquisition module includes a main shooting unit, a top shooting unit and a front shooting unit;

[0019] The main shooting unit is used to receive the main acquisition information of the main shooting camera, wherein the main acquisition information at least includes a top view of the material;

[0020] The overhead shooting unit is used to receive the supplementary recording and collection information of the overhead shooting camera, wherein the supplementary recording and collection information at least includes a side view of the material;

[0021] The front-view unit is used to receive travel information collected by the front-view camera, wherein the travel information at least includes a front view of the material.

[0022] Furthermore, the acquisition module also includes a shape acquisition unit, which is used to acquire the shape of the material, wherein the shape acquisition unit includes a scanning node and a shooting node.

[0023] Furthermore, the splicing module includes

[0024] Obtain any two types of information from the main collection information, supplementary collection information, or itinerary collection information at the same time node;

[0025] The overlapping information is obtained by overlapping any two of the main collected information, the supplementary collected information, or the itinerary collected information.

[0026] Furthermore, the screening module includes:

[0027] Obtain the coincidence information and check the coincidence information according to the preset inspection conditions;

[0028] If the inspection fails, the selected main collected information or supplementary collected information or information that is not overlapped in the itinerary collected information will be overlapped again, and a supplementary identification photo will be obtained.

[0029] Furthermore, the recognition module is used to recognize the spliced ​​identification photo or the supplementary identification photo, including:

[0030] Identify the identification photo or supplementary identification photo according to preset instructions.

[0031] Furthermore, the preset instruction includes a color instruction or a shape instruction.

[0032] Furthermore, the top view, side view, and front view have the same resolution and size.

[0033] Furthermore, the overlap information includes:

[0034] A new photo is created by overlapping any two pictures from the top view, side view, and front view.

[0035] Furthermore, the main shooting unit, the overhead shooting unit and the front shooting unit all collect the main collected information, the supplementary collected information and the travel collected information at the same time.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] The high-frequency electronic camera system provided in this embodiment is applied to scenarios where color sorting is performed based on industrial cameras as collectors, especially in scenarios where high speed, high resolution, and high recognition rate are required.

[0038] In specific implementation, the camera used to shoot the top view of the material is defined as the main camera, the camera used to shoot the side view of the material is defined as the top view camera, and the camera used to shoot the front view of the material is defined as the front camera. The corresponding material is the shooting target, the area before entering the shooting area is defined as the travel area, and the area after passing the shooting area is defined as the supplementary recording area;

[0039] The area corresponding to the main camera is the shooting area, the area corresponding to the front camera is the travel area, and the area corresponding to the overhead camera is the supplementary recording area.

[0040] When the material passes through the travel area, shooting area and supplementary recording area via the conveyor device, the corresponding main camera, front camera and overhead camera will all capture images of the material. Of course, the image may also include other objects, which are not considered here.

[0041] Preset instructions can quickly realize the classification and color recognition of materials. Secondly, by setting industrial cameras with different shooting angles, even if a camera has problems or the picture is not clear under high-speed shooting, the above method can be used to remedy the problem, greatly improving the shooting speed of industrial cameras and the screening speed of color sorters. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

[0043] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0044] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. 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 making creative efforts shall fall within the scope of protection of the present invention.

[0045] Therefore, the detailed description of the embodiments of the present invention provided in the following figures is not intended to limit the scope of the claimed invention but is merely representative of selected embodiments of the present invention.

[0046] The high-frequency electronic camera system provided in this embodiment is applied to scenarios where color sorting is performed based on industrial cameras as collectors, especially in scenarios where high speed, high resolution, and high recognition rate are required.

[0047] In specific implementation, the camera used to shoot the top view of the material is defined as the main camera, the camera used to shoot the side view of the material is defined as the top view camera, and the camera used to shoot the front view of the material is defined as the front camera. The corresponding material is the shooting target, the area before entering the shooting area is defined as the travel area, and the area after passing the shooting area is defined as the supplementary recording area;

[0048] The area corresponding to the main camera is the shooting area, the area corresponding to the front camera is the travel area, and the area corresponding to the overhead camera is the supplementary recording area.

[0049] When the material passes through the travel area, shooting area and supplementary recording area via the conveyor device, the corresponding main camera, front camera and overhead camera will all capture images of the material. Of course, the image may also include other objects, which are not considered here.

[0050] like Figure 1 As shown, a high-frequency electronic camera system comprises:

[0051] The acquisition module is used to acquire the material image information transmitted by the color sorter; the material image information includes: main acquisition information, supplementary acquisition information and trip acquisition information;

[0052] In a further specific implementation, the acquisition module includes a main shooting unit, a top-down shooting unit, and a front-facing shooting unit; correspondingly, the main shooting unit is used to receive the main acquisition information of the main shooting camera, wherein the main acquisition information at least includes a top view of the material; the top-down shooting unit is used to receive the supplementary acquisition information of the top-down shooting camera, wherein the supplementary acquisition information at least includes a side view of the material; the front-facing shooting unit is used to receive the travel acquisition information of the front-facing camera, wherein the travel acquisition information at least includes a front view of the material;

[0053] In a specific implementation, the main shooting unit, the overhead shooting unit, and the front shooting unit control the corresponding actuators to collect the main collection information, the supplementary collection information, and the travel collection information at the same time;

[0054] More specifically, the actuators are industrial cameras of the same model and with the same settings. During specific execution, due to the same settings, the shooting effect, shooting size, and shooting resolution can be guaranteed to be the same to the greatest extent possible.

[0055] In specific implementations, the model of the industrial camera is mainly based on the type selected during specific implementation and is not specifically limited here.

[0056] In a further specific implementation, the collection unit further includes a shape collection unit, wherein the shape collection unit is deployed at the starting end of the color sorter transmission device. Specifically, the shape collection unit controls the scanning node and the shooting node to collect the shape of the material transmitted by the transmission device;

[0057] Specifically, the scanning node may be a laser scanner with scanning modeling, and the shooting node may be an intelligent camera with pattern recognition;

[0058] Acquire the acquisition data of the smart camera and the scanning data of the laser scanner, wherein the acquisition data includes material video model data and material screen data, and the scanning data includes material scanning model data;

[0059] The shape acquisition unit uses built-in modeling software to build a video model and a scanning model based on the material video model data and the material scanning model data respectively;

[0060] Obtain the feature values ​​of the video model and the scanning model through a neural network algorithm;

[0061] There are two situations that may occur at this time;

[0062] In the first case, if the eigenvalues ​​corresponding to the video model are different from those corresponding to the scan model, the material video data is obtained and analyzed using a pre-trained video analysis neural algorithm to obtain analysis features.

[0063] Select and analyze the features as eigenvalues, where the eigenvalues ​​include the number of faces and the number of edges of the material;

[0064] For example, when the cross-section of the material is a trapezoid, the corresponding characteristic value of the material includes 6 faces and 12 edges; when the material is spherical, the corresponding characteristic value of the material includes 1 face and 0 edges;

[0065] In a specific implementation, if the first situation occurs, the transmission device of the color sorter will reduce the transmission speed. Specifically, depending on the computing power of the video analysis neural algorithm running device in the application scenario, the corresponding transmission device of the color sorter will reduce the transmission speed differently. Therefore, the present invention does not make specific requirements on whether the transmission device of the color sorter will reduce the transmission speed.

[0066] On the one hand, it can improve the resolution of the acquisition; on the other hand, it can provide time for the operation of the video analysis neural algorithm, avoiding the problem of materials being transported to the travel area before their characteristics are recognized;

[0067] In the second case, if the eigenvalue corresponding to the video model is the same as the eigenvalue corresponding to the scanning model, the eigenvalue corresponding to any one of the models is output, where the models include the video model and the scanning model.

[0068] Before obtaining the feature values ​​of the video model and the scanning model through the neural network algorithm, the neural network algorithm needs to be trained. Specifically:

[0069] Collect several sample video models, sample scan models and sample pictures in advance, and intelligently match the sample video models, sample scan models and sample pictures through a neural network algorithm to obtain the feature values ​​of the sample pictures;

[0070] Among them, the sample pictures are pictures with characteristic values, and the sample pictures are all selected from the material video data;

[0071] More specifically, the neural network algorithm is a convolutional neural network operation circuit, which, when implemented, includes:

[0072] An external memory for storing the image to be processed; the external memory includes at least one of the following:

[0073] Double rate synchronous dynamic random access memory, synchronous dynamic random access memory.

[0074] Internal memory includes static memory array,

[0075] The static memory array includes multiple static memories, each of which is used to store different data

[0076] A direct access unit is connected to the external memory and is used to read the image to be processed and transmit the read data to the control unit;

[0077] a control unit connected to the direct access unit and configured to store data into an internal memory;

[0078] Internal memory, connected to the control unit, for caching data;

[0079] The arithmetic unit is connected to the internal memory and is used to read data from the internal memory and perform convolution and pooling operations;

[0080] The operation unit includes a convolution operation unit, a pooling operation unit, a buffer unit and a buffer control unit;

[0081] The convolution operation unit is used to perform convolution operation on the data and transmit the convolution result to the pooling operation unit;

[0082] The pooling operation unit is connected to the convolution operation unit, and is used to perform a pooling operation on the convolution result and store the obtained pooling result in the buffer unit;

[0083] The buffer control unit is used to store the pooling result in the internal memory through the buffer unit or in the external memory through the direct access unit.

[0084] More specifically, the number of operation units is at least two. When a cascade structure is adopted between the operation units, the data of the nth layer is cached in the internal memory after the convolution and pooling operation of the nth operation unit, and the (n+1)th operation unit takes out the operated data and performs the convolution and pooling operation of the (n+1)th layer, where n is a positive integer.

[0085] When the various operation units are connected in parallel, each operation unit processes a portion of the image to be processed respectively, and each operation unit uses the same convolution kernel to perform parallel convolution pooling operations.

[0086] When the various operation units are connected in parallel, each operation unit performs different feature extraction on the image to be processed, and each operation unit uses a different convolution kernel to perform parallel convolution pooling operations.

[0087] When there are two operation units, the two operation units respectively extract the contour information and detail information of the image to be processed.

[0088] A splicing module is used to randomly retrieve any two types of information from the main collected information, the supplementary collected information, or the itinerary collected information and splice them to form an identification photo;

[0089] Specifically, any two of the main collected information, supplementary collected information, or itinerary collected information at the same time node are obtained;

[0090] In a specific implementation, by obtaining any two of the main collected information, the supplementary collected information, or the trip collected information, any two photos of the top view, the side view, or the front view taken at the same time can be obtained. Moreover, because the above-mentioned actuators are industrial cameras of the same model and the same settings, in a specific implementation, due to the same settings, it can be ensured that the shooting effect, the shooting size, and the shooting resolution are the same to the greatest extent, so that the sizes of the two randomly selected photos are the same.

[0091] The overlapping information is obtained by overlapping any two of the main collected information, the supplementary collected information, or the itinerary collected information.

[0092] Specifically, by overlapping the two photos, an identification photo can be obtained, wherein the identification photo is the overlap information;

[0093] A screening module is used to screen the identification photos;

[0094] Specifically, the coincidence information is obtained and checked according to the preset checking conditions;

[0095] If the inspection fails, the selected main collected information or supplementary collected information or information that is not overlapped in the itinerary collected information will be overlapped again, and a supplementary identification photo will be obtained.

[0096] At this point, there are two types of situations, specifically divided into:

[0097] In the first category, if the screening conditions are met, the identification photo will be sent to the recognition module for identification;

[0098] In the second category, if the screening conditions are not met, the identification photo is supplemented with details to obtain a supplementary identification photo, and the supplementary identification photo is sent to the recognition module for recognition;

[0099] In specific implementation, the screening conditions include photo resolution, photo size, and the location of the photo calibration point. If any of the following conditions occurs, the screening conditions are considered not met;

[0100] (1) The resolution of the identification photo generated after the overlap is different from the resolution of any two images in the selected top view, side view, and front view;

[0101] (2) The photo size of the identification photo generated after the overlap is different from the photo size of any two pictures in the selected top view, side view, and front view;

[0102] (3) The positions of the photo calibration points in the identification photos generated after the overlap do not overlap;

[0103] The calibration point in the photo is the lower right corner of the default output image after the industrial camera takes the image and is 3 mm away from the two corresponding sides of the lower right corner, and the calibration point is marked on the side with the image;

[0104] When the second type of situation occurs, the photo obtained for identification does not meet one or more of the corresponding filtering conditions. Specifically,

[0105] When the identified photo does not meet (1), a photo is randomly removed and the removed photo is marked as the first removed photo. At this time, the remaining photos in the identified photo are marked as the first remaining photos. At this time, the first remaining photo and the first removed photo are overlapped in the unselected top view, side view or front view respectively;

[0106] The overlapping photos are screened, and if all of them meet the screening conditions, the overlapping photo corresponding to the first remaining photo is selected as the supplementary identification photo;

[0107] When the identified photo does not meet (2), a photo is randomly removed and the removed photo is marked as the second removed photo. At this time, the remaining photos in the identified photo are marked as the second remaining photos. At this time, the second remaining photos and the second removed photos are overlapped in the unselected top view, side view or front view respectively;

[0108] The overlapping photos are screened, and if all of them meet the screening conditions, the overlapping photo corresponding to the second remaining photo is selected as the supplementary identification photo;

[0109] When the identified photo does not meet (3), a photo is randomly removed and the removed photo is marked as the third removed photo. At this time, the remaining photos in the identified photo are marked as the third remaining photos. At this time, the third remaining photo and the third removed photo are overlapped in the unselected top view, side view or front view respectively;

[0110] The overlapping photos are screened, and if all of them meet the screening conditions, the overlapping photo corresponding to the first remaining photo is selected as the supplementary identification photo;

[0111] If the above photos still do not meet the screening conditions after supplementation, the corresponding top view will be selected as the supplementary recognition photo and an accuracy alarm message will be generated;

[0112] The recognition module is used to recognize the spliced ​​identification photos or supplementary identification photos, including:

[0113] Identify the identification photo or supplementary identification photo according to preset instructions.

[0114] Preset instructions include color instructions or shape instructions;

[0115] In the specific implementation, the color instruction or shape instruction can be set in advance.

[0116] a. Extract the color characteristics of the target material and match it with the color of the template image;

[0117] Specifically, the template image color is a preset color instruction;

[0118] More specifically, the RGB color space of the target material is converted to the HSV color space, and after removing the pixels with low saturation, the histogram is obtained based on the H feature and its probability density distribution map is calculated;

[0119] The Meanshift algorithm is used to find the center point with the largest amount of color information based on the template histogram;

[0120] The search window centered on the center point obtained in the above step is divided into four sub-windows: upper left, lower left, upper right, and lower right, and the total amount of color of the probability density map is compared respectively.

[0121] b. Extract the shape features of the target material and match them with the shape of the template image;

[0122] Specifically, the shape of the template image is a pre-set shape instruction;

[0123] More specifically, the target image is converted into a grayscale image;

[0124] Perform dilation and erosion morphological filtering to remove independent noise and increase image continuity;

[0125] A two-level pyramid of the target is constructed using a bidirectional extraction method;

[0126] The Sobel operator is used to perform edge detection on the pyramid images at all levels to obtain the contour pyramid image;

[0127] Perform fast Hausdorff distance transform on the main contour pyramid image to obtain a distance mapping image that can reflect the closest distance between each pixel and the edge point set;

[0128] Use the edge point set of the template image to perform a traversal search on the distance map image of the pyramid image.

[0129] c. When the above matching meets the set conditions, the target material and the template are matched and the target identification is completed;

[0130] More specifically, the upper pyramid distance matching is performed first. If its Hausdorff distance is less than the threshold, it is determined that the matching is successful at this pyramid level, and the matching operation of the lower pyramid level is performed until the target is found or the traversal is completed.

[0131] The color matching condition in c is: when the total color value accounts for 40% to 200% of the total color value of the template image, it is determined that the color match is successful;

[0132] Preset instructions can quickly realize the classification and color recognition of materials. Secondly, by setting industrial cameras with different shooting angles, even if a camera has problems or the picture is not clear under high-speed shooting, the above method can be used to remedy the problem, greatly improving the shooting speed of industrial cameras and the screening speed of color sorters.

[0133] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0134] In the embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the module division is merely a logical functional division, and other division methods may be used in actual implementation. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the method of this embodiment.

[0135] It is also obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0136] Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the claims are intended to be embraced therein. Any reference to a figure in a claim should not be construed as limiting the claim to which it relates.

[0137] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices recited in a system claim may also be implemented by a single unit or device through software or hardware. Second-order terms are used to indicate names and do not imply any particular order.

[0138] Finally, it should be noted that the above embodiments are only used to illustrate the technical method of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A high-frequency electronic camera system, characterized in that: include: Acquisition module, used to collect material image information transmitted from the color sorter; The material image information includes: main collection information, supplementary collection information and itinerary collection information; A splicing module is used to randomly retrieve any two types of information from the main collected information, the supplementary collected information, or the itinerary collected information and splice them to form an identification photo; A screening module is used to screen the identification photos; If the screening conditions are met, the identification photo will be sent to the recognition module for identification; If the screening conditions are not met, the identification photo is supplemented with details to obtain a supplementary identification photo, and the supplementary identification photo is sent to the recognition module for recognition; The recognition module is used to recognize the spliced ​​identification photos or supplementary identification photos.

2. A high-frequency electronic camera system according to claim 1, characterized in that: The acquisition module includes a main shooting unit, a top shooting unit and a front shooting unit; The main shooting unit is used to receive the main acquisition information of the main shooting camera, wherein the main acquisition information at least includes a top view of the material; The overhead shooting unit is used to receive the supplementary recording and collection information of the overhead shooting camera, wherein the supplementary recording and collection information at least includes a side view of the material; The front-view unit is used to receive travel information collected by the front-view camera, wherein the travel information at least includes a front view of the material.

3. A high-frequency electronic camera system according to claim 1, characterized in that: The acquisition module further includes a shape acquisition unit, which is used to acquire the shape of the material. The shape acquisition unit includes a scanning node and a shooting node.

4. A high-frequency electronic camera system according to claim 1, characterized in that: The splicing module includes Obtain any two types of information from the main collection information, supplementary collection information, or itinerary collection information at the same time node; The overlapping information is obtained by overlapping any two of the main collected information, the supplementary collected information, or the itinerary collected information.

5. A high-frequency electronic camera system according to claim 1, characterized in that: The screening module includes: Obtain the coincidence information and check the coincidence information according to the preset inspection conditions; If the inspection fails, the selected main collected information or supplementary collected information or information that is not overlapped in the itinerary collected information will be overlapped again, and a supplementary identification photo will be obtained.

6. A high-frequency electronic camera system according to claim 1, characterized in that: The recognition module is used to recognize the spliced ​​identification photo or the supplementary identification photo, including: Identify the identification photo or supplementary identification photo according to preset instructions.

7. A high-frequency electronic camera system according to claim 6, characterized in that: The preset instructions include color instructions or shape instructions.

8. A high-frequency electronic camera system according to claim 2, characterized in that: The top view, side view, and front view have the same resolution and size.

9. A high-frequency electronic camera system according to claim 5, characterized in that: The overlap information includes: a new photo obtained by overlapping any two pictures in the top view, the side view and the front view.

10. A high-frequency electronic camera system according to claim 2, characterized in that: The main shooting unit, the overhead shooting unit and the front shooting unit all collect the main collected information, the supplementary collected information and the travel collected information at the same time.

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