A vehicle electronic rearview mirror working state detection system and method

Abstract

The application provides a detection system for working state of vehicle electronic rearview mirror, comprising: an image acquisition unit for acquiring frame image of vehicle body of fixed marker; the detection unit is used for saving reference frame image and its template image acquired by the image acquisition unit in normal state, and reference frame feature vector set extracted from the reference frame image; real-time frame feature vector set is extracted from real-time frame image acquired by the image acquisition unit, real-time frame feature vector set and reference frame feature vector set are compared, and whether the image acquisition unit is moved or blocked is judged. The application also provides a detection method for working state of vehicle electronic rearview mirror, through matching current frame feature vector set and reference feature vector of reference frame image, whether vehicle electronic rearview mirror camera is moved or blocked can be judged, so that whether the moving vehicle electronic rearview mirror camera is in safe working state can be quickly and effectively judged.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of automotive electronics, in particular to a vehicle electronic rearview mirror working state detection system and method. BACKGROUND

[0002] Compared with the traditional vehicle optical rearview mirror, the vehicle electronic rearview mirror uses a small and compact camera to replace the traditional mirror surface. Since the volume and wind resistance of the vehicle are reduced, the fuel consumption and wind noise are also reduced. The vehicle video captured by the camera is played on the screen in the vehicle, which eliminates the risk of blocking the traditional mirror surface rearview mirror by the vehicle window glass in snowy weather. Moreover, due to the wide field of view of the camera, the blind area of the traditional rearview mirror can be effectively avoided, and the safety is increased.

[0003] However, compared with the traditional vehicle mirror surface rearview mirror, the damage of the camera of the vehicle electronic rearview mirror, the blocking of the camera, the movement of the camera, and the death of the camera will all affect the working of the vehicle electronic rearview mirror. Therefore, it is of great significance to perform real-time safety detection on the vehicle electronic rearview mirror system. SUMMARY

[0004] In order to solve the problems existing in the prior art, the purpose of the present application is to provide a vehicle electronic rearview mirror working state detection system and method, which can quickly and effectively determine whether the camera of the moving vehicle electronic rearview mirror is in a safe working state.

[0005] To achieve the above-mentioned purpose, the present application provides a vehicle electronic rearview mirror working state detection system, comprising:

[0006] An image acquisition unit is configured to acquire a frame image of a vehicle body of a fixed marker;

[0007] The detection unit is configured to save a reference frame image and a template image thereof acquired by the image acquisition unit in a normal state, and a reference frame feature vector set extracted from the reference frame image; extract a real-time frame feature vector set from a real-time frame image acquired by the image acquisition unit, compare the real-time frame feature vector set with the reference frame feature vector set, and determine whether the image acquisition unit is moved or blocked.

[0008] Further, the image acquisition unit is a camera of a vehicle electronic rearview mirror.

[0009] Further, the detection unit comprises,

[0010] An image conversion module is configured to set a non-vehicle body part in the reference frame image as black and a vehicle body part as white to generate a template image.

[0011] a feature extraction module, configured to extract a reference frame feature vector set from the reference frame image by using a feature extraction operator; and to obtain a feature area image by performing point-by-point operation on the real-time frame image and the template image, and to extract a real-time frame feature vector set from the feature area image by using the feature extraction operator;

[0012] a storage module, configured to save the real-time reference frame image, the template image, and the reference frame feature vector set;

[0013] a feature matching module, configured to compare the real-time frame feature vector set and the reference frame feature vector set, and to determine whether the image acquisition unit is moved or blocked.

[0014] Further, the feature matching module reads the reference frame feature vector set from the storage module, and performs feature matching on the real-time frame feature vector set and the reference frame feature vector set, and determines that the image acquisition unit is moved or blocked if the number of successfully matched feature vectors is less than a preset threshold.

[0015] Further, the detection unit compares the real-time frame image acquired by the image acquisition unit and a plurality of reference frame images one by one, and determines whether the image acquisition unit is abnormal.

[0016] Further, the detection unit determines that the image acquisition unit is abnormal if it is detected that the real-time frame image is identical to at least one of the plurality of reference frame images.

[0017] Further, the detection unit comprises,

[0018] a comparison module, configured to compare the real-time frame image with a plurality of reference frame images, and to determine that the image acquisition unit is abnormal if it is detected that the real-time frame image is identical to at least one of the plurality of reference frame images.

[0019] Further, the comparison module sends the current frame image to the storage module when it is determined that the image acquisition unit is abnormal, and the storage module stores the current frame image and deletes the oldest frame image.

[0020] To achieve the above object, the application further provides a vehicle electronic rearview mirror working state detection method, comprising:

[0021] acquiring and saving a reference frame image acquired by the image acquisition unit in a normal state, a template image generated by using the reference frame image, and a reference frame feature vector set extracted from the reference frame image;

[0022] comparing the acquired real-time frame image with the reference frame image, and determining whether the image acquisition unit is abnormal;

[0023] According to the real-time frame image and the template image, a real-time frame feature vector set is extracted by point-by-point operation;

[0024] The reference frame feature vector set and the real-time frame feature vector set are matched to determine whether the image acquisition unit is moved or blocked.

[0025] Further, the step of acquiring and saving the reference frame image acquired by the image acquisition unit in the normal state, the template image generated by the reference frame image, and the reference frame feature vector set extracted from the reference frame image further comprises:

[0026] The frame image of the fixed marker of the vehicle body acquired in the normal state is saved as the reference frame image;

[0027] The non-vehicle body part in the frame image is set to black, and the vehicle body part is set to white to generate a template image and save it;

[0028] The reference frame feature vector set is extracted from the reference frame image by using a feature extraction operator.

[0029] Further, the step of comparing the acquired real-time frame image with the reference frame image to determine whether the image acquisition unit is malfunctioning further comprises:

[0030] The real-time frame image is compared with a plurality of reference frame images, and if it is detected that the real-time frame image is the same as at least one of the plurality of reference frame images, it is determined that the image acquisition unit is abnormal

[0031] Further, the step of extracting a real-time frame feature vector set according to the real-time frame image and the template image by point-by-point operation further comprises:

[0032] The acquired real-time frame image is operated with the template image point by point to obtain a feature area image;

[0033] The frame feature vector set is extracted from the feature area image by using a feature extraction operator.

[0034] Further, the step of matching the reference frame feature vector set and the real-time frame feature vector set to determine whether the image acquisition unit is moved or blocked further comprises:

[0035] The real-time frame feature vector set and the reference frame feature vector set are matched, and if the number of successfully matched feature vectors is less than a set threshold, it is determined that the image acquisition unit is moved or blocked.

[0036] To achieve the above-mentioned purpose, the application also provides an automobile electronic control chip, which comprises the vehicle electronic rearview mirror working state detection system as described above.

[0037] To achieve the above object, the application further provides a circuit board comprising the automobile electronic control chip.

[0038] To achieve the above object, the application further provides an electronic device comprising at least one processor and a memory.

[0039] The memory stores computer execution instructions.

[0040] The at least one processor executes the computer execution instructions stored in the memory, so that the at least one processor executes the steps of the vehicle electronic rearview mirror working state detection method.

[0041] To achieve the above object, the application provides a computer readable storage medium, which stores computer instructions, and when the computer instructions are executed, the steps of the vehicle electronic rearview mirror working state detection method are executed.

[0042] The vehicle electronic rearview mirror working state detection system and method provided by the application can determine whether the vehicle electronic rearview mirror camera is moved or blocked by matching the current frame feature vector set extracted from the current frame image and the reference feature vector of the reference frame image, so that whether the vehicle electronic rearview mirror camera in movement is in a safe working state can be quickly and effectively determined.

[0043] Other features and advantages of the application will be described in the following description, and some will become apparent from the description, or will be understood by those skilled in the art through implementation of the application. BRIEF DESCRIPTION OF DRAWINGS

[0044] The accompanying drawings are intended to provide further understanding of the application, and constitute a part of the specification, and together with the embodiments of the application, serve to explain the application, and do not constitute a limitation on the application. In the drawings:

[0045] Figure 1 The figure is a vehicle electronic rearview mirror working state detection system architecture diagram according to an embodiment of the application.

[0046] Figure 2 The figure is a vehicle electronic rearview mirror working state detection method flow chart according to an embodiment of the application.

[0047] Figure 3 The figure is an electronic device structure schematic diagram according to an embodiment of the application. DETAILED DESCRIPTION

[0048] Embodiments of the present application will be described below in greater detail with reference to the accompanying drawings. While certain embodiments of the present application are shown in the drawings, it is understood that the present application can be embodied in various forms and should not be interpreted in a limited sense as set forth in the description below. Rather, these embodiments are provided so that the present application will be thoroughly and completely understood as a whole. It is understood that the drawings of the present application and the embodiments are for illustrative purposes only and are not intended to limit the scope of the present application.

[0049] It should be understood that each step recited in the method embodiments of the present application can be performed in different orders and / or in parallel. In addition, the method embodiments can include additional steps and / or omit the steps shown. The scope of the present application is not limited in this respect.

[0050] The term "comprising" and variations thereof as used herein are used inclusively, i.e., "comprising but not limited to". The term "based on" is "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Related terms are defined in the description below.

[0051] It should be noted that the terms "first", "second", and the like in the present application are merely intended to distinguish different devices, modules or units, and do not imply the order or interdependence of the functions performed by these devices, modules or units.

[0052] It should be noted that the terms "one", "multiple" in the present application are illustrative and not restrictive, and those skilled in the art should understand that "one" or "multiple" should be understood as "one or more" unless otherwise explicitly indicated in the context. "Multiple" should be understood as two or more.

[0053] The names of the messages or information exchanged between the various units and modules in the embodiments of the present application are merely illustrative and not intended to limit the scope of the messages or information.

[0054] In the following, embodiments of the present application will be described in detail with reference to the accompanying drawings.

[0055] Embodiment 1

[0056] Figure 1 For the vehicle electronic rearview mirror working state detection system according to the present application, as shown in Figure 1 the vehicle electronic rearview mirror working state detection system 1 of the embodiments of the present application includes: an image acquisition unit 10; a detection unit 20, including: an image conversion module 21, a comparison module 22, a storage module 23, a feature extraction module 24, and a feature matching module 25.

[0057] The image acquisition unit 10 is configured to acquire a frame image of the vehicle body including the fixed marker.

[0058] In the embodiment, the frame image acquired by the image acquisition unit 10 under normal conditions is saved to the storage module 23 as a reference frame image, and the frame image acquired in real time is sent to the image conversion module 21 as a real-time frame image (Image_Cf).

[0059] In the embodiment, the image acquisition timing is once per frame (frm), and each frame is 60 fps (Frames Per Second).

[0060] In the embodiment, the fixed marker includes, but is not limited to, a vehicle handle, a vehicle window, and the like.

[0061] The detection unit 20 is configured to detect whether the image acquisition unit 10 is abnormal.

[0062] The image conversion module 21 is configured to convert the received frame image into a frame grayscale image, generate a template image from the frame image acquired by the image acquisition unit 10 under normal conditions (reference frame image), extract a reference frame feature vector set from the reference frame image, send the reference frame image, the template image, and the reference frame feature vector set to the storage module 23 for storage, send the real-time frame image acquired by the image acquisition unit 10 to the comparison module 22, and acquire a real-time frame feature vector set according to the real-time frame image acquired by the image acquisition unit 10 and the template image, and send the real-time frame feature vector set to the feature matching module 25.

[0063] The template image is a mask (Image_Mask) generated by setting the non-vehicle body part in the frame image of the vehicle body including the fixed marker acquired by the image acquisition unit 10 under normal conditions to black (gray value of 0) and the vehicle body part to white (gray value of 255). The vehicle body feature point information is a reference frame feature vector set (Points_Ref) extracted from the reference frame image using a feature extraction operator. The feature extraction operator can use, but is not limited to, an ORB (Oriented Fast and Rotated Brief), a FAST (Features from Accelerated Segment Test), a SURF (Speeded Up Robust Features), a SIFT (Scale Invariant Feature Transform), and the like.

[0064] The comparison module 22 receives the real-time frame image, reads the plurality of previously stored reference frame images from the storage module 23, and compares the real-time frame image with the plurality of previously stored frame images one by one. If the real-time frame image is completely consistent with a reference frame image, it is determined that the image acquisition unit 10 is abnormal (for example, a fault), and the comparison module 22 sends the real-time frame grayscale image to the storage module 23, which stores the real-time frame grayscale image and deletes the oldest frame grayscale image. If no completely consistent image is found, it is determined that the image acquisition unit 10 is normal.

[0065] When it is determined that the image acquisition unit 10 is normal, the comparison module 22 sends the real-time frame image to the feature extraction module 24.

[0066] The feature extraction module 24 receives the real-time frame image and reads the mask from the storage module 23, and performs a point-by-point AND operation on the real-time frame image and the mask to extract a feature region image (Image_Key) in the same region as the original vehicle body position in the real-time frame image. The feature extraction module 24 uses a feature extraction operator to extract real-time frame feature points (real-time frame feature vector set Points_Cf) in the feature region image and sends them to the feature matching module 25.

[0067] The feature matching module 25 receives the real-time frame feature vector set and reads the reference frame feature vector set from the storage module 23. The feature matching module 25 uses a matching algorithm such as BFMatcher (Brute Force Matcher) or FlannBasedMatcher to perform feature matching between the real-time frame feature vector set and the reference frame feature vector set. If the percentage of successfully matched feature vectors is less than a first threshold T1, it is determined that the vehicle electronic rearview mirror camera is blocked or moved. Specifically, when the percentage of successful matches is greater than or equal to the first threshold T1, the feature matching module 25 determines that the image acquisition unit 10 is normal; when the percentage of successful matches is less than the first threshold T1 and greater than or equal to a second threshold T2, the feature matching module 25 determines that the image acquisition unit 10 is slightly shaken; when the percentage of successful matches is less than the second threshold T2 and greater than or equal to a third threshold T3, the feature matching module 25 determines that the image acquisition unit 10 is moved; and when the percentage of successful matches is less than the third threshold T3, the feature matching module 25 determines that the image acquisition unit 10 is blocked.

[0068] In the embodiment of the present application, the image acquisition unit 10 is a vehicle electronic rearview mirror, which includes a vehicle electronic rearview mirror camera, generally using a wide-angle lens, with a large field of view, so that after installation, it generally does not need to be moved, and the need to adjust the viewing angle is generally moved or scaled by image processing algorithms, so it can be considered that the lens is not moved relative to the vehicle body after installation. Then the specific area of the vehicle electronic rearview mirror camera collecting images will be fixed to display the relevant content of the vehicle itself, such as the vehicle body, wheels, door handles, or bumpers, etc. The position of these contents in the vehicle electronic rearview mirror camera image does not move greatly with the movement of the vehicle.

[0069] In addition, in the embodiment of the present application, when the comparison module 22 judges that the image acquisition unit 10 has an abnormality, the result can be sent to, for example, a control unit to display the result on a display panel. In addition, when the feature matching module 25 judges that the image acquisition unit 10 has an abnormality such as being blocked, shaken, moved, etc., the specific abnormality can be sent to, for example, a control unit to display the result on a display panel.

[0070] According to the embodiment of the present application, by comparing the real-time frame image with the previous multiple frame gray images, it can be judged whether the image acquisition unit 10 has an abnormality, and further, by matching the real-time frame feature vector set in the feature area image corresponding to the mask in the real-time frame gray image with the reference feature vector of the mask, it can be judged the specific abnormality of the image acquisition unit 10. By detecting the change of the position of the key feature points in these specific areas, it can quickly and effectively judge whether the vehicle electronic rearview mirror camera in motion is in a safe working state.

[0071] Embodiment 2

[0072] Figure 2 For the flow chart of the vehicle electronic rearview mirror working state detection method according to the present application, the following will be described with reference to Figure 2 , the vehicle electronic rearview mirror working state detection method of the present application will be described in detail.

[0073] In step 101, a real-time frame image (Image_Cf) of a vehicle body including a fixed marker is acquired. Specifically, the image acquisition unit 10 collects a real-time frame image of a vehicle body including a fixed marker, and sends it to the image conversion module 21. In the embodiment of the present application, the image acquisition timing is once per frame, and each frame is 60fps.

[0074] In step 102, the real-time frame image is converted into a real-time frame gray image, and saved. Specifically, the image conversion module 21 converts the received real-time frame image into a real-time frame gray image, and sends it to the comparison module 22.

[0075] In step 103, the real-time frame image is compared with the plurality of reference frame images one by one. Specifically, the storage module 23 stores a template image and body feature point information (reference frame feature vector set) in advance. The template image is a mask (Image_Mask) generated by setting the non-body part of the body frame image acquired by the image acquisition unit 10 in a normal state to black (gray value of 0) and the body part to white (gray value of 255). The body feature point information is a reference frame feature vector set (Points_Ref) extracted based on the template image using a feature extraction operator. In addition, the storage module 23 stores a plurality of reference frame images. The comparison module 22 reads the stored plurality of reference frame images from the storage module 23 upon receiving the real-time frame image, and compares the real-time frame image with the stored plurality of reference frame images one by one.

[0076] In step 104, it is determined whether there is a reference frame image identical to the real-time frame image. If a reference frame image identical to the real-time frame image appears, it is determined that the image acquisition unit 10 is abnormal (for example, malfunction), and step 109 is performed. If no identical image appears, it is determined that the image acquisition unit 10 is normal, and step 105 is performed.

[0077] In step 105, a feature area image of the same area as the original body position in the real-time frame image is extracted based on the real-time frame image and the mask, and a real-time frame feature vector set of the feature area image is extracted.

[0078] Specifically, the feature extraction module 24 receives the real-time frame image, reads the mask from the storage module 23, and performs a point-by-point AND operation on the real-time frame image and the mask to extract a feature area image (Image_Key) of the same area as the original body position in the real-time frame gray image. The feature extraction module 24 extracts a real-time frame feature vector set (Points_Cf) in the feature area image using a feature extraction operator, and sends it to the feature matching module 25.

[0079] In step 106, the real-time frame feature vector set is subjected to feature matching with the reference frame feature vector set. Specifically, the feature matching module 25 receives the real-time frame feature vector set, and reads the reference frame feature vector set from the storage module 23. The feature matching module 25 performs feature matching between the real-time frame feature vector set and the reference frame feature vector set using a matching algorithm such as BFMatche or FlannBasedMatcher.

[0080] At step 107, it is judged whether the percentage of matching in step 106 is less than a first threshold T1. If the percentage of the number of successfully matched feature vectors is less than the first threshold T1, it is judged that the vehicle electronic rearview mirror camera is abnormal, and step 108 is executed. If the percentage of the number of successfully matched feature vectors is greater than or equal to the first threshold T1, it is judged that the vehicle electronic rearview mirror camera is normal, and step 109 is executed.

[0081] At step 108, the specific situation of the vehicle electronic rearview mirror camera being abnormal is determined. Specifically, when the percentage of successful matching is less than the first threshold T1 and greater than or equal to a second threshold T2, the feature matching module 25 judges that the vehicle electronic rearview mirror camera is slightly shaken. When the percentage of successful matching is less than the second threshold T2 and greater than or equal to a third threshold T3, the feature matching module 25 judges that the vehicle electronic rearview mirror camera is moved. When the percentage of successful matching is less than the third threshold T3, the feature matching module 25 judges that the vehicle electronic rearview mirror camera is blocked.

[0082] At step 109, the real-time frame image is stored and the oldest frame grayscale image is deleted. Specifically, the comparison module 22 sends the real-time frame image to the storage module 23, while the storage module 23 deletes the oldest frame image and returns to step 101.

[0083] According to the embodiments of the present application, by comparing the real-time frame image with the previously stored multiple frame images, it can be judged whether the image acquisition unit (i.e., the vehicle electronic rearview mirror camera) is abnormal. If no abnormality of the image acquisition unit is found, by matching the current frame feature vector set in the feature area image corresponding to the template image (mask) in the current frame image with the reference feature vector of the template image, the specific abnormal situation (such as movement or being blocked) of the image acquisition unit can be judged. The vehicle electronic rearview mirror camera in movement can be quickly judged whether it is in a safe working state, and the reliability of the functional safety detection of the vehicle electronic rearview mirror camera in movement is improved.

[0084] Embodiment 3

[0085] In the embodiments of the present application, an automobile electronic control chip is also provided, which comprises the vehicle electronic rearview mirror working state detection system as described above.

[0086] Embodiment 4

[0087] In the embodiments of the present application, a circuit board is also provided, which comprises the automobile electronic control chip as described above.

[0088] Embodiment 5

[0089] In the embodiments of the present application, an electronic device is also provided, which comprises the vehicle electronic rearview mirror working state detection system as described above. Figure 3As shown, the vehicle electronic rearview mirror working state detection device comprises at least one processor 301 and a memory 302;

[0090] The memory 302 stores computer execution instructions.

[0091] The at least one processor 301 executes the computer execution instructions stored in the memory 302, so that the at least one processor 301 executes the steps of the vehicle electronic rearview mirror working state detection method as described above.

[0092] In the embodiments of the present application, a computer readable storage medium is also provided, which stores computer instructions, and when the computer instructions are executed, the steps of the vehicle electronic rearview mirror working state detection method described above are executed.

[0093] Those skilled in the art can understand that the above only describes the preferred embodiments of the present application and is not used to limit the present application, although the present application has been described in detail with reference to the foregoing embodiments, and those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments or make equivalent replacements for some technical features. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A vehicle electronic rearview mirror working status detection system, characterized in that, include: The image acquisition unit is used to acquire frame images of the vehicle body of the fixed marker; The detection unit is used to store the reference frame image and its template image acquired by the image acquisition unit under normal conditions, as well as the reference frame feature vector set extracted from the reference frame image; If a real-time frame image is detected to be identical to at least one of the multiple reference frame images, it is determined that the image acquisition unit is malfunctioning; a real-time frame feature vector set is extracted from the real-time frame image acquired by the image acquisition unit, and the real-time frame feature vector set is compared with the reference frame feature vector set to determine whether the image acquisition unit has moved or been blocked. The template image is a mask generated based on a vehicle frame image including fixed markers collected under normal conditions, with non-vehicle parts set to black and vehicle parts set to white. The reference frame feature vector set is the vehicle body feature point information extracted based on the template image using a feature extraction operator; The real-time frame feature vector set is a set of real-time frame feature vectors extracted from the real-time frame image based on the template image, representing the feature area image of the same region as the original vehicle body position.

2. The vehicle electronic rearview mirror working status detection system according to claim 1, characterized in that, The image acquisition unit is a vehicle electronic rearview mirror camera.

3. The vehicle electronic rearview mirror working status detection system according to claim 1, characterized in that, The detection unit includes, The image conversion module sets the non-vehicle parts of the reference frame image to black and the vehicle parts to white, generating a template image; The feature extraction module uses feature extraction operators to extract a set of reference frame feature vectors from the reference frame image; The real-time frame image and the template image are processed point by point to obtain a feature region image, and a feature extraction operator is used to extract the real-time frame feature vector set from it. The storage module is used to save the reference frame image, the template image, and the reference frame feature vector set; The feature matching module is used to compare the real-time frame feature vector set and the reference frame feature vector set to determine whether the image acquisition unit has moved or been blocked.

4. The vehicle electronic rearview mirror working status detection system according to claim 3, characterized in that, The feature matching module reads the reference frame feature vector set from the storage module and performs feature matching between the real-time frame feature vector set and the reference frame feature vector set. If the number of successfully matched feature vectors is less than a set threshold, it is determined that the image acquisition unit has moved or been blocked.

5. The vehicle electronic rearview mirror working status detection system according to claim 1, characterized in that, The detection unit compares the real-time frame image acquired by the image acquisition unit with multiple reference frame images one by one to determine whether the image acquisition unit has an abnormality.

6. The vehicle electronic rearview mirror working status detection system according to claim 3, characterized in that, The detection unit includes, The comparison module is used to compare the real-time frame image with a plurality of reference frame images. If the real-time frame image is found to be the same as at least one of the plurality of reference frame images, it is determined that the image acquisition unit has malfunctioned.

7. The vehicle electronic rearview mirror working status detection system according to claim 6, characterized in that, When the comparison module determines that the image acquisition unit is abnormal, it sends the current frame image to the storage module, which stores the current frame image and deletes the oldest frame image.

8. A method for detecting the working status of a vehicle electronic rearview mirror, used in the vehicle electronic rearview mirror working status detection system according to any one of claims 1-7, comprising: Acquire and save the reference frame image acquired by the image acquisition unit under normal conditions, the template image generated using the reference frame image, and the reference frame feature vector set extracted from the reference frame image; The acquired real-time frame image is compared with the reference frame image to determine whether the image acquisition unit has malfunctioned; the real-time frame feature vector set is extracted by performing point-by-point calculations based on the real-time frame image and the template image. The reference frame feature vector set is matched with the real-time frame feature vector set to determine whether the image acquisition unit has moved or been blocked.

9. The method for detecting the working status of a vehicle electronic rearview mirror according to claim 8, characterized in that, The step of acquiring and saving the reference frame image acquired by the image acquisition unit under normal conditions, the template image generated using the reference frame image, and the reference frame feature vector set extracted from the reference frame image further includes: Save the frame image of the fixed marker on the vehicle body under normal conditions as the reference frame image; Set the non-vehicle parts of the reference frame image to black and the vehicle parts to white, and generate a template image and save it. The feature vector set of the reference frame is extracted from the reference frame image using a feature extraction operator.

10. The method for detecting the working status of a vehicle electronic rearview mirror according to claim 8, characterized in that, The step of comparing the acquired real-time frame image with the reference frame image to determine whether the image acquisition unit has malfunctioned further includes: The real-time frame image is compared with multiple reference frame images. If the real-time frame image is found to be the same as at least one of the multiple reference frame images, it is determined that the image acquisition unit is malfunctioning.

11. The method for detecting the working status of a vehicle electronic rearview mirror according to claim 8, characterized in that, The step of extracting the real-time frame feature vector set by performing point-by-point calculations based on the real-time frame image and the template image further includes: The acquired real-time frame image and the template image are processed point by point to obtain the feature region image; The feature vector set of the reference frame is extracted from the feature region image using a feature extraction operator.

12. The method for detecting the working status of a vehicle electronic rearview mirror according to claim 8, characterized in that, The step of matching the reference frame feature vector set with the real-time frame feature vector set to determine whether the image acquisition unit has moved or been blocked further includes: The real-time frame feature vector set is matched with the reference frame feature vector set. If the number of successfully matched feature vectors is less than a set threshold, it is determined that the image acquisition unit has moved or is blocked.

13. An automotive electronic control chip, characterized in that, The system includes the vehicle electronic rearview mirror working status detection system as described in any one of claims 1 to 7.

14. A circuit board, characterized in that, Including the automotive electronic control chip as described in claim 13.

15. An electronic device, characterized in that, include: At least one processor and memory; The memory stores computer-executed instructions; The at least one processor executes computer execution instructions stored in the memory, causing the at least one processor to perform the steps of the vehicle electronic rearview mirror working status detection method according to any one of claims 8 to 12.

16. A computer-readable storage medium, characterized in that, It stores computer instructions, which, when executed, perform the steps of the vehicle electronic rearview mirror working status detection method according to any one of claims 8 to 12.

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