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Research on Tire Surface Damage Detection Method Based on Image Processing.
Chen, Jiaqi; Li, Aijuan; Zheng, Fei; Chen, Shanshan; He, Weikai; Zhang, Guangping.
Afiliação
  • Chen J; School of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, China.
  • Li A; School of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, China.
  • Zheng F; Research and Development Department, Shandong Wonderful Intelligent Technology Co., Ltd., Jinan 250101, China.
  • Chen S; Research and Development Department, Shandong Wonderful Intelligent Technology Co., Ltd., Jinan 250101, China.
  • He W; School of Aeronautics, Shandong Jiaotong University, Jinan 250357, China.
  • Zhang G; Research and Development Department, Shandong Wonderful Intelligent Technology Co., Ltd., Jinan 250101, China.
Sensors (Basel) ; 24(9)2024 Apr 26.
Article em En | MEDLINE | ID: mdl-38732884
ABSTRACT
The performance of the tire has a very important impact on the safe driving of the car, and in the actual use of the tire, due to complex road conditions or use conditions, it will inevitably 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 "salt and pepper" 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China
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