基于计算机视觉的织物疵点检测技术研究进展  

Progress of fabric defect detection techniques based on computer vision

作　　者：楼少敏[1] 朱彦[2] 俞晓群[2] 

机构地区：[1]浙江科技学院中德学院,杭州310023 [2]浙江科技学院服装学院,杭州310023

出　　处：《丝绸》2011年第6期17-21,共5页Journal of Silk

基　　金：浙江省科技计划项目(2007C21147)

摘　　要：对基于计算机视觉的织物疵点检测技术进行回顾,介绍了灰度共生矩阵法,局部二值模式算法,邻域关联分析,自组织映射,支持向量机,学习向量量化分类器,多分类器组合和决策融合等算法等在图像预处理,特征提取、分类和识别等方面的应用情况,着重讨论了一种基于多数投票原则的多分类器决策融合技术,试验结果证实该技术有较高精确性。In this paper,various methods of fabric defect dectection based on computer vision are reviewed. This article describes the image preprocessing,feature extraction,classificaition and identification for the various algorithms,such as Gray level co-occurrence Matrix,Local Binary Patterns,Contextual Analysis, Self-organizing Maps,Support Vector Method,Learning Vector Quantization,Multi-classifier combination, decision fusion,etc.A multi-classifier decision fusion technique based on majority voting is mainly discussed. Empirical results indicate the high accuracy of the presented approach.

关 键 词：计算机视觉 织物疵点检测 决策融合 

分 类 号：TS101.9[轻工技术与工程—纺织工程]