Tire wear determination method and determination system
By acquiring and preprocessing tire images, extracting wear features and comparing them with safety thresholds, and combining wear distribution and shape to determine the tire wear type, the problem of subjectivity and low efficiency in existing tire wear inspection technologies is solved, achieving efficient and accurate wear detection and type determination.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-28
- Publication Date
- 2026-03-17
AI Technical Summary
Existing tire wear inspection methods mainly rely on visual inspection, which is highly subjective, inefficient, and vehicle sensors cannot directly detect wear, making it impossible to accurately identify the wear condition and type.
By acquiring images of the tire tread and sidewall, preprocessing is performed to improve image quality, and wear features such as groove depth and wear surface are extracted. The wear type is determined by comparing the wear features with a safety threshold and combining the distribution area and edge shape of the wear surface.
It enables automatic and accurate tire wear detection and type determination, reduces human subjectivity, improves detection efficiency and accuracy, provides maintenance suggestions, avoids safety hazards, and reduces maintenance costs.
Smart Images
Figure CN121685973A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of wear detection, in particular to a tire wear determination method and a determination system. BACKGROUND
[0002] Tire abnormal wear refers to a phenomenon that a certain part of a tire is worn more obviously than other parts due to factors such as four-wheel positioning, tire installation, and unbalanced loading of goods during vehicle driving. Tire abnormal wear not only shortens the service life of the tire and increases the cost of replacing the tire, but also affects the handling performance and driving safety of the vehicle. Therefore, accurately identifying the wear state of the tire is an important link for accurately determining the performance boundary of the vehicle.
[0003] In related technologies, the tire wear inspection method mainly relies on visual method, which is highly subjective and low in efficiency. Quantitative measurement needs to use special tools, and the existing sensors (such as tire pressure sensor TPMS) of the vehicle can only detect tire pressure and cannot directly detect wear, and cannot diagnose the wear type. SUMMARY
[0004] The present application aims to at least solve the technical problems in the related art. To this end, the present application provides a tire wear determination method, which is beneficial to accurately identifying the wear condition and wear type of the tire.
[0005] The present application also provides a determination system.
[0006] The tire wear determination method of the first aspect embodiment of the present application comprises: Collecting a tread image and a sidewall image of a tire, and preprocessing the tread image and the sidewall image to improve the image quality; Extracting wear features from the tread image and the sidewall image, wherein the wear features include a plurality of groove depths and a wear surface; Comparing the average value of the plurality of groove depths with a safety threshold value, and if the average value is less than or equal to the safety threshold value, determining that the tire has abnormal wear; When the tire has abnormal wear, determining the wear type of the tire according to the distribution area and the edge shape of the wear surface.
[0007] The tire wear determination method according to the embodiments of the present application has at least the following beneficial effects: the tire wear determination method can collect a tread image and a sidewall image of a tire to be detected by a camera, and pre-process the tread image and the sidewall image to reduce noise of the tread image and the sidewall image and enhance the tread image and the sidewall image, thereby improving image quality of the sidewall image and the tread image, and then the tire wear determination method can extract wear features from the sidewall image and the tread image, the wear features at least including depths of a plurality of grooves and a wear surface, the tire wear determination method can compare an average value of the depths of the plurality of grooves with a safety threshold value to determine whether the tire has abnormal wear, the tire wear determination method can realize automatic and high-precision wear detection through image comparison, can improve objectivity and accuracy of the tire wear determination method, the tire wear determination method determines that the tire has abnormal wear, and determines a wear type of the tire according to a distribution area and an edge shape of the wear surface, that is, the tire wear determination method can not only detect wear of the tire, but also determine the wear type, to improve pertinence of tire wear detection.
[0008] According to some embodiments of the present application, the pre-processing of the tread image and the sidewall image to improve image quality includes: The median filter and the Gaussian filter are used to filter the tread image and the sidewall image to suppress noise; The contrast of the grooves and the wear surface in the tread image and the sidewall image is enhanced, and the outlines of the grooves and the wear surface are clearer.
[0009] According to some embodiments of the present application, the wear features are extracted from the tread image and the sidewall image, the wear features including depths of a plurality of grooves and a wear surface, and the extraction includes: The edges of top ends and bottom ends of the grooves are extracted from the sidewall image, and the depths of the grooves are calculated according to pixel distances between the edges of the top ends and the edges of the bottom ends; According to a corresponding relationship between the tread image and the sidewall image, a wear surface corresponding to a specific groove depth is extracted; The tread image and / or the sidewall image are subjected to image segmentation to separate the wear surface from a non-wear area, and a ratio of each wear surface to a total tread is calculated.
[0010] According to some embodiments of the present application, the average value of the depths of the plurality of grooves is compared with the safety threshold value, and if the average value is less than or equal to the safety threshold value, it is determined that the tire has abnormal wear, and the comparison includes: A wear limit mark block in the grooves is extracted from the sidewall image, and the safety threshold value is calculated according to a pixel distance between an edge of a top end of the wear limit mark block and an edge of a bottom end of the wear limit mark block; The average value of the depths of the plurality of grooves is calculated, and the average value is compared with the safety threshold value.
[0011] According to some embodiments of the present application, when the tire has abnormal wear, the wear type of the tire is determined according to the distribution area and the edge shape of the wear surface, including: The ratio of the wear surface of the central area of the tire to the total tread is calculated as a first ratio, and the ratio of the wear surface of the two side areas of the tire to the total tread is calculated as a second ratio; If the first ratio is greater than the second ratio, and the difference is greater than a first threshold value, the wear type is determined to be central wear.
[0012] According to some embodiments of the present application, when the tire has abnormal wear, the wear type of the tire is determined according to the distribution area and the edge shape of the wear surface, including: The ratio of the wear surface of the central area of the tire to the total tread is calculated as a first ratio, and the ratio of the wear surface of the two side areas of the tire to the total tread is calculated as a second ratio; If the first ratio is less than the second ratio, and the difference is greater than a second threshold value, the wear type is determined to be bilateral wear.
[0013] According to some embodiments of the present application, when the tire has abnormal wear, the wear type of the tire is determined according to the distribution area and the edge shape of the wear surface, including: The edge shape of the wear surface is collected; If the edge shape of the wear surface has a jagged feature, the wear type is determined to be feather wear.
[0014] According to some embodiments of the present application, the average value of the plurality of groove depths is compared with a safety threshold value, and if the average value is less than or equal to the safety threshold value, it is determined that the tire has abnormal wear, including: A first correspondence relationship data of the type of the tire and the safety threshold value is constructed; According to the type of the detected tire, the corresponding safety threshold value is selected in the first correspondence relationship data; And / or, the wear features are extracted from the tread image and the sidewall image, the wear features including a plurality of groove depths and a wear surface, including: A second correspondence relationship data of the type of the tire and the tread shape is constructed; According to the type of the detected tire, the corresponding tread shape is selected in the second correspondence relationship data; According to the comparison of the tread shape and the tread image, the wear surface is extracted from the tread image.
[0015] According to some embodiments of the present application, the tire wear determination method further includes: A third correspondence relationship data of the wear type and the maintenance suggestion is constructed; According to the determined wear type, the corresponding maintenance suggestion is selected in the third correspondence relationship data; The maintenance suggestion is conveyed to the user or the maintenance personnel.
[0016] The determination system of the second aspect embodiment of the present application, the image acquisition module is configured to acquire the tread image and the sidewall image of the tire; The image acquisition module is configured to acquire the tread image and the sidewall image of the tire; The preprocessing module is configured to preprocess the tread image and the sidewall image to improve the image quality; The image feature extraction module is configured to extract the wear feature in the tread image and the sidewall image, the wear feature including a plurality of groove depths and a wear surface; The wear analysis module is configured to compare the average value of the plurality of groove depths with a safety threshold value, and if the average value of the plurality of groove depths is less than or equal to the safety threshold value, it is determined that the tire has abnormal wear; The wear type analysis module is configured to determine the wear type of the tire according to the distribution area and the edge shape of the wear surface when the tire has abnormal wear.
[0017] Additional aspects and advantages of the present application will be made apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS
[0018] The present application will be further described below in conjunction with the accompanying drawings and embodiments, wherein: Figure 1 The overall flowchart of the tire wear determination method of an embodiment of the present application; Figure 2 The flowchart of the tire wear determination method of an embodiment of the present application; Figure 3 The flowchart of the tire wear determination method of an embodiment of the present application for preprocessing the tread image and the sidewall image; Figure 4 The flowchart of the tire wear determination method of an embodiment of the present application for image feature extraction of the tread image and the sidewall image; Figure 5 The flowchart of the tire wear determination method of an embodiment of the present application for comparing the average value with the safety threshold value; Figure 6 The flowchart of the tire wear determination method of an embodiment of the present application for determining the wear type as central wear; Figure 7 The flowchart of the tire wear determination method of an embodiment of the present application for determining the wear type as two-side wear; Figure 8 The flowchart of the tire wear determination method of an embodiment of the present application for determining the wear type as feather wear; Figure 9A flow chart of constructing first corresponding relationship data of the tire wear determination method of one embodiment of the present application; Figure 10 A flow chart of constructing second corresponding relationship data of the tire wear determination method of one embodiment of the present application; Figure 11 A flow chart of constructing third corresponding relationship data of the tire wear determination method of one embodiment of the present application. DETAILED DESCRIPTION
[0019] Embodiments of the present application are described in detail below with reference to the accompanying drawings, in which like reference numerals refer to like elements or elements having the same function throughout the description of the drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as a limitation of the present application.
[0020] In the description of the present application, it should be understood that the orientation description, such as the orientation or position relationship indicated by up, down, etc. is based on the orientation or position relationship shown in the drawings, and is only for the purpose of facilitating the description of the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation of the present application.
[0021] In the description of the present application, multiple refers to two or more. If there is a description of first, second, it is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or the sequence of technical features indicated.
[0022] In the description of the present application, unless otherwise explicitly limited, the words such as setting, installing, connecting, etc. should be broadly understood, and the person skilled in the art can reasonably determine the specific meaning of the above words in the present application in combination with the specific content of the technical solution.
[0023] Referring to Figures 1 to 11 The tire wear determination method of one embodiment of the present application includes the following steps: Step S100, collecting a tread image and a sidewall image of a tire, and pre-processing the tread image and the sidewall image to improve image quality; Step S200, extracting wear features in the tread image and the sidewall image, the wear features including a plurality of groove depths and a wear surface; Step S300, comparing the average value of the plurality of groove depths with a safety threshold value, and if the average value is less than or equal to the safety threshold value, determining that the tire has abnormal wear; Step S400, when the tire has abnormal wear, determining the wear type of the tire according to the distribution area and the edge shape of the wear surface.
[0024] In step S100, the tire wear determination method can be applied to a vehicle repair shop, and the vehicle to be detected can enter the repair shop, and the front image and the side image of the tire to be detected are obtained by two industrial cameras respectively, so as to obtain the tread image and the sidewall image of the tire to be detected, so as to realize automatic acquisition and detection of the image without human intervention, which is beneficial to improve the detection efficiency.
[0025] Then the tire wear determination method can be preprocessed by filtering and enhancement processing, so as to reduce the noise of the sidewall image and the tread image, and play an enhancement effect, which can reduce the human intervention, thereby reducing the human subjectivity of determination, and making the result more accurate and reliable.
[0026] In step S200, the tire wear determination method can extract wear features from the sidewall image and the tread image, wherein the wear features include a plurality of groove depths and wear surfaces. By means of quantitative feature extraction, human subjective error can be avoided as much as possible, and data support is provided for subsequent wear analysis and wear type analysis.
[0027] In step S300, after the plurality of groove depths are extracted from the sidewall image and the tread image, the average value of the plurality of groove depths is obtained by averaging the plurality of groove depths, and the average value of the plurality of groove depths is compared with the safety threshold value. If the average value is less than or equal to the safety threshold value, it means that the wear of the tire has exceeded the safety standard, and the tire is determined to have abnormal wear.
[0028] In step S400, when the tire wear determination method determines that the tire has abnormal wear, the wear type of the tire can be determined according to the distribution area and the edge shape of the wear surface, that is, the tire wear determination method can not only determine whether the tire has abnormal wear, but also diagnose the type of wear, so as to provide fundamental maintenance guidance for the user, and realize the technical leap from detection to diagnosis.
[0029] The tire wear determination method can diagnose the type of wear of the tire, so as to provide early warning of wear for the user, avoid safety hazards, and reduce the overall maintenance cost.
[0030] It can be understood that the tire wear determination method in step S100 preprocesses the tread image and the sidewall image to improve the image quality, including the following steps: Step S110, a median filter and a Gaussian filter are used to filter the tread image and the sidewall image to suppress noise; Step S120, enhancing the contrast of the grooves and wear surfaces in the tread image and the sidewall image, so that the outlines of the grooves and wear surfaces are clearer.
[0031] In step S110, the tire wear determination method can effectively suppress the salt and pepper noise and Gaussian noise generated in the acquisition and transmission process of the tire side image and the tread image by the combination of the median filter and the Gaussian filter, that is, play a good noise suppression role.
[0032] In step S120, the tire wear determination method can also use the limited contrast adaptive histogram equalization algorithm to enhance the contrast of the grooves and the wear surface in the tread image and the tire side image, so that the profile of the grooves and the wear surface is more clear, and at the same time, it can avoid over amplifying noise.
[0033] The tire wear determination method can denoise and enhance the collected tire side image and tread image through a unique image processing algorithm to improve the image quality and facilitate subsequent feature extraction.
[0034] It can be understood that the tire wear determination method extracts wear features in the tread image and the tire side image in step S200, and the wear features include a plurality of groove depths and wear surfaces, including the following steps: Step S210, the edges of the top end and the bottom end of the groove are extracted in the tire side image, and the groove depth is calculated according to the pixel distance between the edges of the top end and the edges of the bottom end; Step S220, according to the corresponding relationship between the tread image and the tire side image, the wear surface corresponding to a specific groove depth is extracted; Step S230, image segmentation is performed on the tread image and / or the tire side image, the wear surface and the un-worn area are separated, and the ratio of each wear surface to the total tread is calculated.
[0035] In step S210, the tire wear determination method can identify the edges of the top end and the bottom end of the groove in the tire side image through an edge detection algorithm, and then calculate the pixel distance between the edges of the top end and the edges of the bottom end of the groove to obtain the groove depth.
[0036] In step S220, the tire wear determination method can collect the tire side image and the tread image through two industrial cameras with relatively fixed positions, so that the tire side image and the tread image have a certain corresponding relationship, and then the tire wear determination method can extract the wear surface corresponding to a specific groove depth in the tread image.
[0037] The numerical value of the specific groove depth is usually less than a certain preset value, that is, the tread with the specific groove depth generally has a large wear, and the tire wear determination method can define the tread corresponding to the specific groove depth as a wear surface.
[0038] In step S240, the tire wear determination method can separate the wear surface from the unworn area by using image segmentation techniques (such as Otsu threshold segmentation method), and then calculate the ratio of the pixel area of each wear surface to the total pixel area of the analyzed tire surface as a quantitative indicator of the wear surface, thereby providing data support for subsequent wear analysis and wear type analysis.
[0039] It can be understood that in step S300, the tire wear determination method compares the average value of the plurality of groove depths with the safety threshold value, and if the average value is less than or equal to the safety threshold value, it is determined that the tire has abnormal wear, including the following steps: In step S310, the wear limit marker block in the groove is extracted in the sidewall image, and the safety threshold value is calculated according to the pixel distance between the top edge and the bottom edge of the wear limit marker block. In step S320, the average value of the plurality of groove depths is calculated, and the average value is compared with the safety threshold value.
[0040] In step S310, the tire wear determination method can extract the wear limit marker block in the groove in the sidewall image as a reference for the safety threshold value. Specifically, the tire wear determination method can identify the top edge and the bottom edge of the wear limit marker block in the sidewall image by using an edge detection algorithm, and then calculate the safety threshold value according to the pixel distance between the top edge and the bottom edge of the wear limit marker block.
[0041] For example, the tire wear determination method can take the pixel distance between the top edge and the bottom edge of the wear limit marker block and the accumulation of the safety pre-addition value as the safety threshold value, that is, it indicates that the tire has already been worn significantly, but has not reached the normal service life of the tire.
[0042] In step S320, the tire wear determination method can calculate the average value of the plurality of groove depths, and compare the average value with the safety threshold value, so as to determine whether the tire has abnormal wear problems.
[0043] It can be understood that in step S400, when the tire has abnormal wear, the tire wear determination method determines the wear type of the tire according to the distribution area and the edge shape of the wear surface, including the following steps: In step S410, the ratio of the wear surface in the central area of the tire to the total tire surface is calculated as a first ratio, and the ratio of the wear surface in the two side areas of the tire to the total tire surface is calculated as a second ratio. In step S420, if the first ratio is greater than the second ratio, and the difference is greater than a first threshold value, it is determined that the wear type is central wear.
[0044] In step S410, the tire wear determination method can calculate the ratio of the worn surface in the central region of the tire to the total tread as a first ratio, and calculate the ratio of the worn surface in the two side regions of the tire to the total tread as a second ratio.
[0045] In step S420, the tire wear determination method can compare the first ratio with the second ratio, if the first ratio is greater than the second ratio, and the difference is greater than a first threshold, i.e. the wear area ratio of the central region of the tread is significantly higher than that of the two side regions, and determine that the central wear, which is usually related to the tire pressure being too high.
[0046] It can be understood that the tire wear determination method in step S400 determines the wear type of the tire according to the distribution region and edge shape of the worn surface when the tire has abnormal wear, including the following steps: Step S430, calculating the ratio of the worn surface in the central region of the tire to the total tread as a first ratio, and calculating the ratio of the worn surface in the two side regions of the tire to the total tread as a second ratio; Step S440, if the first ratio is less than the second ratio, and the difference is greater than a second threshold, determining that the wear type is bilateral wear.
[0047] In step S430, the tire wear determination method can calculate the ratio of the worn surface in the central region of the tire to the total tread as a first ratio, and calculate the ratio of the worn surface in the two side regions of the tire to the total tread as a second ratio.
[0048] In step S440, the tire wear determination method can compare the first ratio with the second ratio, if the first ratio is less than the second ratio, and the difference is greater than a second threshold, i.e. the wear area ratio of the two side regions of the tread is significantly higher than that of the central region, and determine that the two side wear, which is usually related to the tire pressure being too low.
[0049] It should be noted that the first threshold and the second threshold can be derived from pre-experiments or by data collection, and are not specifically limited here.
[0050] It can be understood that the tire wear determination method in step S400 determines the wear type of the tire according to the distribution region and edge shape of the worn surface when the tire has abnormal wear, including the following steps: Step S450, collecting the edge shape of the worn surface; Step S460, if the edge shape of the worn surface has a jagged feature, determining that the wear type is feather wear.
[0051] In step S450 and step S460, the tire wear determination method determines by analyzing the edge shape of the tread block, if the edge of the tread block has obvious "feather-like" or "sawtooth-like" features, it is determined as feather wear, which is usually related to wheel alignment (such as toe angle anomaly).
[0052] It can be understood that the tire wear determination method extracts wear features in the tread image and the sidewall image in step S200, the wear features include a plurality of groove depths and a wear surface, including the following steps: Step S240, constructing a second correspondence relationship data of the type of tire and the tread shape; Step S250, selecting the corresponding tread shape in the second correspondence relationship data according to the detected type of tire; Step S260, extracting the wear surface in the tread image according to the comparison between the tread shape and the tread image.
[0053] The tire wear determination method can construct the second correspondence relationship data of the type of tire and the tread shape in advance, when the tire is detected, the user can input the test type of tire in advance, and select the corresponding tread shape in the second correspondence relationship data.
[0054] In the extraction of wear features, the tire wear determination method can compare the corresponding tread shape with the tread image, so as to extract the wear surface with obvious wear in the collected tread image.
[0055] It can be understood that the tire wear determination method compares the average value of the plurality of groove depths with the safety threshold in step S300, if the average value is less than or equal to the safety threshold, it is determined that the tire has abnormal wear, including the following steps: Step S310, constructing a first correspondence relationship data of the type of tire and the safety threshold; Step S320, selecting the corresponding safety threshold in the first correspondence relationship data according to the detected type of tire; The tire wear determination method can construct the first correspondence relationship data of the type of tire and the safety threshold in advance, when the tire is detected, the user can input the test type of tire in advance, and select the corresponding safety threshold in the first correspondence relationship data.
[0056] In the wear analysis, the tire wear determination method can compare the average value of the plurality of groove depths with the preset safety threshold, so as to assist in determining whether the tire tread has abnormal wear.
[0057] For example, the tire wear determination method can select the safety threshold of the corresponding tire as 1.6 mm in the first corresponding relationship data, and when the extracted average groove depth value is lower than the safety threshold, the determination of abnormal wear is triggered.
[0058] It can be understood that the tire wear determination method further comprises the following steps: Step S500, constructing third corresponding relationship data of wear type and maintenance suggestion; Step S600, selecting the corresponding maintenance suggestion in the third corresponding relationship data according to the determined wear type; Step S700, conveying the maintenance suggestion to the user or the maintenance personnel.
[0059] The tire wear determination method can pre-construct the third corresponding relationship data of wear type and maintenance suggestion, and after the tire wear determination method determines the wear type of the tire, the corresponding maintenance suggestion can be selected in the third corresponding relationship data, and output to the user or the maintenance personnel in the form of screen display, mobile phone APP push or maintenance work order, so as to realize the function of safety warning.
[0060] The embodiment of the application also proposes a tire wear determination system, which can be used to implement the tire wear determination method of any one of the above-mentioned embodiments, specifically, can implement steps S100-S400 in the above-mentioned embodiment, Figure 2 steps S110-S120 in the above-mentioned embodiment, Figure 3 steps S210-S230 in the above-mentioned embodiment, Figure 4 steps S310-S320 in the above-mentioned embodiment, Figure 5 steps S410-S420 in the above-mentioned embodiment, Figure 6 steps S430-S440 in the above-mentioned embodiment, Figure 7 steps S450-S460 in the above-mentioned embodiment. Figure 8
[0061] Specifically, the tire wear determination system comprises an image acquisition module, a preprocessing module, an image feature extraction module, a wear analysis module and a wear type analysis module.
[0062] The image acquisition module is configured to acquire the tread image and the sidewall image of the tire; The preprocessing module is configured to preprocess the tread image and the sidewall image to improve the image quality; The image feature extraction module is configured to extract wear features in the tread image and the sidewall image, the wear features comprising a plurality of groove depths and a wear surface; The wear analysis module is configured to compare the average value of the plurality of groove depths with a safety threshold, and if the average value of the plurality of groove depths is less than or equal to the safety threshold, it is determined that the tire has abnormal wear. The wear type analysis module is configured to determine the wear type of the tire according to the distribution area and the edge shape of the wear surface when the tire has abnormal wear.
[0063] The tire wear determination system can collect the tread image and the sidewall image of the tire to be detected through the image acquisition module, and pre-process the tread image and the sidewall image through the pre-processing module to reduce the noise of the tread image and the sidewall image and play an enhancement role, thereby improving the image quality of the sidewall image and the tread image. The wear feature extraction module can extract wear features from the sidewall image and the tread image, and the wear features at least include the depth of the plurality of grooves and the wear surface. The wear analysis module can compare the average value of the plurality of groove depths with the safety threshold value to determine whether the tire has abnormal wear. The tire wear determination system can realize automatic and high-precision wear detection through image comparison, and can improve the objectivity and accuracy of the tire wear determination system. When the tire has abnormal wear, the wear type analysis module determines the wear type of the tire according to the distribution area and the edge shape of the wear surface, that is, the tire wear determination system can not only detect the wear of the tire, but also determine the type of the wear to improve the pertinence of the tire wear detection.
[0064] Those skilled in the art will appreciate that embodiments of the present application can be provided as methods, systems, or computer program products. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage media, etc.) having computer usable program code embodied therein.
[0065] The present application is described according to flowcharts and / or block diagrams of the method, device (system), and computer program product of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions.
[0066] Those skilled in the art can understand that all or some of the steps in the above disclosed method, the system can be implemented as software, firmware, hardware and their appropriate combination. Some physical components or all physical components can be implemented as software executed by a processor such as a central processor, a digital signal processor or a microprocessor, or as hardware, or as an integrated circuit such as an application specific integrated circuit.
[0067] The embodiments of the present application are described in detail above with reference to the drawings, but the present application is not limited to the above-described embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the spirit of the present application.
Claims
1. A tire wear determination method characterized by comprising: The method comprises: collecting a tread image and a sidewall image of a tire, and preprocessing the tread image and the sidewall image to improve image quality; extracting wear features from the tread image and the sidewall image, the wear features including a plurality of groove depths and wear surfaces; comparing an average value of the plurality of groove depths with a safety threshold, and determining that the tire has abnormal wear if the average value is less than or equal to the safety threshold; when the tire has the abnormal wear, determining a wear type of the tire according to a distribution area and an edge shape of the wear surface.
2. The tire wear determination method according to claim 1, characterized by, The preprocessing of the tread image and the sidewall image to improve image quality comprises: filtering the tread image and the sidewall image using a median filter and a Gaussian filter to suppress noise; enhancing contrast of grooves and the wear surfaces in the tread image and the sidewall image to make the grooves and the wear surfaces more clear.
3. The tire wear determination method according to claim 1, characterized by, The extraction of the wear features from the tread image and the sidewall image comprises: extracting edges of top ends and bottom ends of the grooves in the sidewall image, and calculating the groove depths according to pixel distances between the edges of the top ends and the edges of the bottom ends; extracting the wear surfaces corresponding to specific groove depths according to a correspondence between the tread image and the sidewall image; performing image segmentation on the tread image and / or the sidewall image to separate the wear surfaces from non-wear areas, and calculating ratios of the wear surfaces to total treads.
4. The tire wear determination method according to claim 1, characterized by, The comparison of the average value of the plurality of groove depths with the safety threshold comprises: extracting wear limit marker blocks in the grooves in the sidewall image, and calculating the safety threshold according to pixel distances between edges of top ends and edges of bottom ends of the wear limit marker blocks; calculating the average value of the plurality of groove depths, and comparing the average value with the safety threshold.
5. The tire wear determination method according to claim 3, characterized by, The determination of the wear type of the tire according to the distribution area and the edge shape of the wear surface when the tire has the abnormal wear comprises: calculating a first ratio of the wear surfaces to total treads in a central area of the tire, and calculating a second ratio of the wear surfaces to total treads in two side areas of the tire; determining that the wear type is central wear if the first ratio is greater than the second ratio and a difference between the first ratio and the second ratio is greater than a first threshold value.
6. The tire wear determination method according to claim 3, characterized by The determination of the wear type of the tire according to the distribution area and the edge shape of the wear surface when the tire has the abnormal wear comprises: calculating a first ratio of the wear surfaces to total treads in a central area of the tire, and calculating a second ratio of the wear surfaces to total treads in two side areas of the tire; determining that the wear type is bilateral wear if the first ratio is less than the second ratio and a difference between the first ratio and the second ratio is greater than a second threshold value.
7. The tire wear determination method according to claim 1, characterized by, The method further comprises: constructing a third corresponding relationship data of the wear type and the maintenance suggestion; selecting the corresponding maintenance suggestion from the third corresponding relationship data according to the determined wear type; and 8. The tire wear determination method according to claim 1, characterized by, delivering the maintenance suggestion to a user or a maintenance personnel. The method further comprises: constructing a third corresponding relationship data of the wear type and the maintenance suggestion; selecting the corresponding maintenance suggestion from the third corresponding relationship data according to the determined wear type; and delivering the maintenance suggestion to a user or a maintenance personnel. The method further comprises: constructing a third corresponding relationship data of the wear type and the maintenance suggestion; 9. The tire wear determination method according to claim 1, characterized by, selecting the corresponding maintenance suggestion from the third corresponding relationship data according to the determined wear type; and delivering the maintenance suggestion to a user or a maintenance personnel. The method further comprises: constructing a third corresponding relationship data of the wear type and the maintenance suggestion; 10. A tire wear determination system characterized by, selecting the corresponding maintenance suggestion from the third corresponding relationship data according to the determined wear type; and delivering the maintenance suggestion to a user or a maintenance personnel. The method further comprises: constructing a third corresponding relationship data of the wear type and the maintenance suggestion; selecting the corresponding maintenance suggestion from the third corresponding relationship data according to the determined wear type; and delivering the maintenance suggestion to a user or a maintenance personnel. The method further comprises: constructing a third corresponding relationship data of the wear type and the maintenance suggestion; selecting the corresponding maintenance suggestion from the third corresponding relationship data according to the determined wear type; and delivering the maintenance suggestion to a user or a maintenance personnel. The method further comprises: constructing a third corresponding relationship data of the wear type and the maintenance suggestion; selecting the corresponding maintenance suggestion from the third corresponding relationship data according to the determined wear type; and delivering the maintenance suggestion to a user or a maintenance personnel. The method further comprises: constructing a third corresponding relationship data of the wear type and the maintenance suggestion; selecting the corresponding maintenance suggestion from the third corresponding relationship data according to the determined wear type; and delivering the maintenance suggestion to a user or a maintenance personnel. The method further comprises: constructing a third corresponding relationship data of the wear type and the maintenance suggestion; selecting the corresponding maintenance suggestion from the third corresponding relationship data according to the determined wear type; and delivering the maintenance suggestion to a user or a maintenance personnel. The method further comprises: constructing a third corresponding relationship data of the wear type and the maintenance suggestion; selecting the corresponding maintenance suggestion from the third corresponding relationship data according to the determined wear type; and delivering the maintenance suggestion to a user or a maintenance personnel. The method further comprises: constructing a third corresponding relationship data of the wear type and the maintenance suggestion; selecting the corresponding maintenance suggestion from the third corresponding relationship data according to the determined wear type; and delivering the maintenance suggestion to a user or a maintenance personnel. The method further comprises: constructing a third corresponding relationship data of the wear type and the maintenance suggestion; selecting the corresponding maintenance suggestion from the third corresponding relationship data according to the determined wear type; and delivering the maintenance suggestion to a user or a maintenance personnel. The method further comprises: constructing a third corresponding relationship data of the wear type and the maintenance suggestion; selecting the corresponding maintenance suggestion from the third corresponding relationship data according to the determined wear type; and delivering the maintenance suggestion to a user or a maintenance personnel.