摘要：In this paper, we present a tire defect detection algorithm based on sparse representation. The dictionary learned from reference images can efficiently represent the test image. As the representation coefficients of normal images have a specific distribution, the local feature can be estimate by comparing representation coefficient distribution. Meanwhile, a coding length is used to measure the global features of representation coefficients. The tire defect is located by both these local and global features. Experimental results demonstrate that the proposed method can accurately detect and locate the tire defects.

摘要：Curve modeling is one of the basic work in computer aided geometric design and computer graphics. For the implicit conic fitting problem in this paper, the research methods that the objective function based on the minimal algebraic distance and geometric distance are summarized. The advantages and disadvantages of every method are analyzed simply, and the applications of the conic fitting are listed.