关键词: 局部可控核（LCK）, 矩阵余弦相似性, 织物疵点, 映射图

Abstract: Aiming at the problem of unobvious contrast between the complex background and the defect in color fabric images, which makes the defect detection difficult, a color fabric defect detection method based on local steering Gaussian kernel is proposed. The input RGB fabric image is converted into the CIEL*a*b color space and the gradient features in each color channel are extracted to construct a structure-adaptive modulation factor by Singular Value Decomposition（SVD）. The shape and the size of the Gaussian function are modulated by the obtained modulation factor, and local steering Gaussian kernel features in the local neighbor of each pixel are extracted to establish a feature matrix for representing the local structures of the input color fabric image. The matrix cosine similarity metric is employed to measure the similarity of kernel feature matrices for obtaining the desired defect map. The experimental results indicate that the proposed method can effectively reveal the singular structures in color fabric images and achieve compelling detection results in comparing with other competitors.

Key words: local steering kernel, matrix cosine similarity, fabric defect detection, defect map