Fabric quality testing using image processing

V. Agilandeswari, J. Anuja, Elizabeth Dona George, R. Prasath
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引用次数: 5

Abstract

The main purpose of this paper is to identify the damaged cloth which may contain defective yarns, colour bleeding, and pores that may be mingled with the good cloth materials at areas such as textile fabric industries, garments, and weaving factories. Automated defect detection for fabrics based on filters is proposed to manage the problem of human visual inspection. The monitoring process is done by a web camera, to capture the details of the cloth. A pre-trained Gabor wavelet network is used to extract the important texture features in the textile fabric. In this defect detection, few specific filters are used to process each frames of the cloth which is being captured by the web camera.
织物质量检测使用图像处理
本文的主要目的是识别在纺织面料工业、服装和织造工厂等领域可能含有缺陷纱线、掉色和可能与好布料混合的毛孔的损坏布料。提出了一种基于过滤器的织物缺陷自动检测方法,以解决人眼视觉检测的问题。监控过程由网络摄像机完成,以捕捉布料的细节。采用预训练Gabor小波网络提取纺织织物的重要纹理特征。在这种缺陷检测中,使用一些特定的过滤器来处理由网络摄像机捕获的织物的每一帧。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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