Abstract:

For a long time, fabric defect detection has been completed by quality inspectors. Meanwhile, the process of defect discrimination is greatly affected by subjective factors and has the problems of low detection efficiency and high cost. With the close combination of computer vision technology and various fields, fabric defect detection system based on vision has gradually become an important solution to replace manual quality inspection. For the fabric defect detection based on vision, this paper reviews the aspects including industry development, general detection standards, overall structure of the system and key technologies in detection algorithms, introduces the existing fabric defect detection products based on vision in the market, analyzes the common defect detection standards and the basic structure of the detection system, and summarizes and compares the research status of image processing and deep learning technology in the field of fabric defect detection in recent years. Finally, the paper summarizes the key problems to be solved, and discusses the possible development direction in the future.

Key words: Defect detection, Fabric detection, Objection recognition, Computer vision, Image processing

摘要：

长久以来，布料的瑕疵检测工作一直由质检员完成，瑕疵判别过程受主观因素影响大,存在检测效率低、成本高等问题。随着计算机视觉技术的发展，基于视觉技术的布料瑕疵检测系统逐渐成为取代人工质检的重要解决方案。针对基于视觉技术的布料瑕疵检测，从行业发展情况、通用检测标准、系统整体结构、检测算法的关键技术等方面进行了综述，介绍了目前市面上已经存在的基于视觉技术的布料瑕疵检测产品，分析了目前常用的瑕疵检测标准与检测系统的基本结构，梳理并对比了近年来图像处理与深度学习技术在布料瑕疵检测领域的研究现状。最后，总结了各方面尚待解决的关键问题，并探讨了未来可能的发展方向。

关键词: 瑕疵检测, 布料检测, 目标识别, 计算机视觉, 图像处理