基于计算机视觉和人工神经网络的丝绸纹理缺陷识别系统

A. Oonsivilai, Nittaya Meeboon
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引用次数: 2

摘要

纺织工业的竞争力取决于产品的质量控制。为了最大限度地降低生产成本,我们努力减少产品的不合格率和生产操作的时间。应保持真丝质地缺陷识别的准确性,以消除任何影响消费者接受真丝质地的异常。本文采用人工神经网络技术实现了真丝纹理缺陷的识别。提出了一种能够提高识别率和简化分类系统架构的特征选择方法。Keywords-silk纹理;计算机视觉;准确;人工神经网络
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Silk Texture Defect Recognition System Using Computer Vision and Artificial Neural Networks
Competiveness of textile industries depends on the quality control of production. In order to minimize production cost, effort is directed towards less defectiveness and time spent on production operations. More accuracy in silk texture defect identification should be maintained so as eliminate any abnormality in the silk texture that hinders its acceptability by the consumer. In this paper, silk texture defect identification is achieved by implementing artificial neural network (ANN) technique. Methodology for feature selection that leads to high recognition rates and to simpler classification systems architectures is presented. Keywords-silk texture; computer-vision; accuracy; artifitial neural network I. INTRODUCTION
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