  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.

Computer Vision and Pattern Recognition;Image and Video Processing