Defect detection of jute fabric using image processing

Abstract

Fabric inspection is important for maintaining the quality of jute fabric. Traditional inspection process for jute fabric defects is human visual inspection which is insufficient and costly. The quality of inspection process for jute fabrics is mainly performed manually. Mostly defects could be detected by the most highly trained inspectors. Manual defect detection is labour intensive, cumbersome, prone to errors and expensive. At present, the fabric defect detection in the jute industry is performed manually. In jute industry improved performance in the inspection of fabrics leads to good product quality and contributes to increased profitability and customer satisfaction. Hence the automatic fabric defect inspection is required to reduce the cost and time waste caused by defects. Automated defect detection is less labour intensive, more accurate, efficient and less costly. The detection of defects of moving jute fabric on inspection table can be identified using Image processing techniques. These image processing techniques are applied and for the input image of a defective fabric frame by frame, conversion into grey scale image, noise filtering, binary image conversion, thresholding are applied on each image of video and the output is obtained in real time. In real time, output will be display the marks on defect area, defect percentage and defect concentration graph of capture length of fabric on inspection table.