Fabric defect detection is a crucial quality control step in the textile manufacturing industry. In this article, a 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%, a precision of 95.8%, and computational speed of 2275 ms.

中文翻译：

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基于Sylvester矩阵的织物疵点检测自动化相似度估计方法

织物缺陷检测是纺织制造业中至关重要的质量控制步骤。本文提出了一种基于Sylvester基于矩阵的相似度方法（SMBSM）的机器视觉系统，以实现缺陷检测过程的自动化。该算法涉及六个阶段，即分辨率匹配，使用直方图规范和基于中值的子图像固定直方图均衡的图像增强，通过对齐和滞后过程进行图像配准，图像相减，边缘检测以及通过以下方式进行故障检测： Sylvester矩阵的等级。实验结果表明，该方法具有鲁棒性，可达到93.4％的精度，95.8％的精度以及2275 ms的计算速度。