Fabric Defect Detection based on GLCM Approach

Abstract

In general, an image of woven fabric sample can be regarded as a typical textured image.The detection of local fabric defects is one of the most captivating problems in computer vision and has received much attention over the years.In the textile industry, careful inspections for woven fabrics have to be carried out because fabric defects may reduce the profit of a company by 45% or 65%.Real time automated fabric defect detection plays a crucial role in the textile manufacturing industry to ensure that the industry meets its high quality standards.Indeed.The production of good quality products is a key issue for increasing profitability and customer satisfaction and thus improving the industry's competitive edge in the global market.If defects in the fabrics are not discovered prior to the garment manufacturing process, significant financial losses can incur.Typically web textile fabric is1-3 m wide and is driven with speed ranging from 20 to 200 m/min.At present, the quality inspection process is manually preformed by experts.However they cannot detect more than 60% of the overall defects for the fabric if it is moving faster than 30 m/min.To increase the quality and homogeneity of fabrics, an automated visual inspection system is needed for better productivity.One way to reduce the total manufacturing cost and to provide a more reliable, objective ,and consistent quality control process is to use an automated visual inspection system to detect possible defects in textile fabrics.However, automated visual inspection becomes a significant challenge due to some specific features pertaining to textile fabrics, for example: (a) Large variety of fabric surfaces has to be examined.(b) Defects may take different forms that are usually difficult to classify.(c) New classes of defects arising from possible changes or aging of machineries in the production process.This paper proposes a new GLCM based technique to address the problem.A sample of different kind of texture defects is shown in Fig. 1.The paper is organized as follows: Section 2introduction the GLCM while Sections 3 describe defect detection system implementation of GLCM approach.Section 4 presents results and discussion.Finally, Section 5 draws the conclusion of the research.Fig. 1.Non-defective and defective fabric images