一种新的图像识别技术在织物缺陷检测中的应用

Bo Cui, Haiying Liu, Tongze Xue
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引用次数: 3

摘要

目前,制造过程中的缺陷检测仍然是由人工完成的,这种方法存在着检测效率低、漏检率高等缺点。这些都严重影响了生产质量,制约了生产效率的进一步提高。本文提出了一种利用Fisher分类器进行计算机图像模式识别的方法,用于织物的缺陷检测和等级评分,并给出了软件编程和测试的实现。测试结果表明,缺陷识别率达94%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of a New Image Recognition Technology in Fabric Defect Detection
At present, defect detection during the manufacturing are still finished by man, there are a lot of weaknesses by this way, such as low detection efficiency, high miss rate. All of these affect the production quality seriously and restrict the further improvement of production efficiency. This paper presents a method using Fisher classifier in computer image pattern recognition for defect detection and grade scoring of fabric, and gives the realization of software programming and testing. The test results show that the defect recognition rate is 94%.
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