Preprocessing using Enhanced Median Filter for Defect Detection in 2D Fabric Images

Abstract—Quality control is one of the basic issues in textile industry. Analysis of texture content in digital images plays an important role in the automated visual inspection of fabric images to detect the defects. The preprocessing stage is an essential initial step in the patterned fabric defect detection system in retaining the important information. And the major problem in processing patterned fabric images is the presence of impulse noise which appears as bright dots or dust particles over the image. This paper proposes an enhanced switching median filter to identify the noisy pixel from the noise free pixel. And the noise is removed based on threshold estimation using genetic algorithm. The performance of the proposed method is evaluated using the metrics such as peak signal to noise ratio, edge preservation capacity and structure preservation capacity and time complexity