论文标题
基于Sylvester矩阵的相似性估计方法用于自动化纺织织物中缺陷检测的方法
Sylvester Matrix Based Similarity Estimation Method for Automation of Defect Detection in Textile Fabrics
论文作者
论文摘要
织物缺陷检测是纺织品制造业的关键质量控制步骤。在本文中，提出了基于Sylvester矩阵的相似性方法（SMBSM）的机器视觉系统以自动化缺陷检测过程。该算法涉及六个阶段，即分辨率匹配，使用直方图规范的图像增强和基于中间均值的次图截止的直方图均衡均衡，通过对齐和滞后过程的图像注册，图像减法，边缘缩减，边缘检测以及通过Sylvester Matrix的等级进行故障检测。实验结果表明，所提出的方法是鲁棒的，准确度为93.4％，精度为95.8％，计算速度为2275 ms。
Fabric defect detection is a crucial quality control step in the textile manufacturing industry. In this article, machine vision system based on the Sylvester Matrix Based Similarity Method (SMBSM) is proposed to automate the defect detection process. The algorithm involves six phases, namely resolution matching, image enhancement using Histogram Specification and Median-Mean Based Sub-Image-Clipped Histogram Equalization, image registration through alignment and hysteresis process, image subtraction, edge detection, and fault detection by means of the rank of the Sylvester matrix. The experimental results demonstrate that the proposed method is robust and yields an accuracy of 93.4%, precision of 95.8%, with 2275 ms computational speed.
