Abstract： The features of tire section were difficult to be extracted by the traditional edge detection methods because of the small difference of gray value between rubbers in the tire section image and the fuzzy boundaries. An algorithm was proposed to extract the features of tire section by combining multilevel fuzzy enhancement, fuzzy Cmeans clustering and morphology. The regions of steel wires were removed to transform the gray values of image. The multilevel fuzzy enhancement was used to increase the contrast between rubbers. The rubber regions were effectively segmented by fuzzy Cmeans clustering, and the boundaries were extracted by morphology. The features of tire section were obtained by stacking the boundary of each region and adding steel wires. Experiments of tire section image were conducted under different light conditions. The results show that the algorithm can effectively solve the problem of small gray value difference between rubbers in the image of tire section and extract the features of tire section with good applicability to different light conditions.
王国林, 周树仁, 李军强. 基于模糊聚类和形态学的轮胎断面特征提取[J]. 江苏大学学报（自然科学版）, 2012, 33(5): 513-517.
WANG Guo-lin, ZHOU Shuren, LI Junqiang. Feature extraction of tire section based on fuzzy clustering and morphology[J]. Journal of Jiangsu University(Natural Science Eidtion)
, 2012, 33(5): 513-517.
2012, Vol. 33 
