关键词: 织物组织, 自动识别, 纱线校正, 灰度共生矩阵, 核模糊聚类

Abstract: This paper employ unsupervised pattern recognition to automatically identify the weave patterns of the fabric based on digital image processing technology. Firstly, it is using shear to correct of the tilt yarn, and gray projection curves of warp and weft to locate crossed points. Then texture features of each crossed-area image are extracted based on gray level co-occurrence matrix(GLCM). In order to reduce the amount of data redundancy, principal component analysis must be implemented to extract the most significant child feature. Finally, the kernel fuzzy C-means clustering is applied to classify the crossed points. The experimental results show that the algorithm can identify the basic fabric weave patterns correctly and output the chart of the identified weave pattern.

Key words: weave pattern, automatic identifying, yarn rectification, gray level co-occurrence matrix, kernel fuzzy clustering