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cause immeasurable wear, scratches and other damage. In order to effectively detect the damage existing in the key parts of the tire, a tire surface damage detection method based on image processing was proposed. In this method, the image of tire side is captured by camera first. Then, the collected images are preprocessed by optimizing the multi-scale bilateral filtering algorithm to enhance the detailed information of the damaged area, and the optimization effect is obvious. Thirdly, the image segmentation based on clustering algorithm is carried out. Finally, the Harris corner detection method is used to capture the \u201csalt and pepper\u201d corner of the target region, and the segmsegmed binary image is screened and matched based on histogram correlation, and the target region is finally obtained. The experimental results show that the similarity detection is accurate, and the damage area can meet the requirements of accurate identification.<\/jats:p>","DOI":"10.3390\/s24092778","type":"journal-article","created":{"date-parts":[[2024,4,26]],"date-time":"2024-04-26T09:26:02Z","timestamp":1714123562000},"page":"2778","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Research on Tire Surface Damage Detection Method Based on Image Processing"],"prefix":"10.3390","volume":"24","author":[{"given":"Jiaqi","family":"Chen","sequence":"first","affiliation":[{"name":"School of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9313-6107","authenticated-orcid":false,"given":"Aijuan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Zheng","sequence":"additional","affiliation":[{"name":"Research and Development Department, Shandong Wonderful Intelligent Technology Co., Ltd., Jinan 250101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shanshan","family":"Chen","sequence":"additional","affiliation":[{"name":"Research and Development Department, Shandong Wonderful Intelligent Technology Co., Ltd., Jinan 250101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weikai","family":"He","sequence":"additional","affiliation":[{"name":"School of Aeronautics, Shandong Jiaotong University, Jinan 250357, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangping","family":"Zhang","sequence":"additional","affiliation":[{"name":"Research and Development Department, Shandong Wonderful Intelligent Technology Co., Ltd., Jinan 250101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,26]]},"reference":[{"key":"ref_1","unstructured":"Li, Z. (2015). Study on the Impact of Damage Defects on the Safety of In-Service Tires. [Master\u2019s Thesis, Qingdao University of Science and Technology]."},{"key":"ref_2","first-page":"187","article-title":"Research on tire defect detection algorithm based on Principal Component Analysis","volume":"36","author":"Zhao","year":"2022","journal-title":"J. Shenyang Univ. Chem. Technol."},{"key":"ref_3","unstructured":"Wang, C. (2019). Development of Tire Surface Defect Detection System. [Master\u2019s Thesis, University of Electronic Science and Technology of China]."},{"key":"ref_4","first-page":"29","article-title":"Research and application of Tire Surface Defect detection System based on Machine vision","volume":"35","author":"Sun","year":"2022","journal-title":"Ind. Control Comput."},{"key":"ref_5","first-page":"35","article-title":"Research on tire tread defect detection method based on RGB image processing","volume":"45","author":"Zheng","year":"2023","journal-title":"Manuf. Autom."},{"key":"ref_6","first-page":"1463","article-title":"A tire defect detection system based on Deep Learning","volume":"50","author":"Gu","year":"2022","journal-title":"Comput. Digit. Eng."},{"key":"ref_7","unstructured":"Sun, Y. (2023). Research on Non-Destructive Detection of Tire Defects Based on Semantic Segmentation. [Master\u2019s Thesis, Qingdao University of Science and Technology]."},{"key":"ref_8","unstructured":"Zhao, M. (2023). Research on Tire Defect Detection Method Based on Object Detection. [Master\u2019s Thesis, Qingdao University of Science and Technology]."},{"key":"ref_9","unstructured":"Yang, S. (2023). Research on Intelligent Nondestructive Testing of Tire Defects Based on Deep Learning. [Master\u2019s Thesis, Qingdao University of Science and Technology]."},{"key":"ref_10","first-page":"17","article-title":"Research review of image segmentation based on clustering","volume":"18","author":"Lin","year":"2022","journal-title":"Comput. Knowl. 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Appl."},{"key":"ref_19","first-page":"185","article-title":"Research on corner detection algorithm based on image edge contour","volume":"30","author":"Jiang","year":"2022","journal-title":"Electron. Des. Eng."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/9\/2778\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:34:10Z","timestamp":1760106850000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/9\/2778"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,26]]},"references-count":19,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["s24092778"],"URL":"https:\/\/doi.org\/10.3390\/s24092778","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,26]]}}}