Defect Classification in Fabric Web Material using LabVIEW

Textile manufacturing is a major industry in India. It is based on the conversion of three types of fibre into yarn which in turn is woven into fabrics. Fabrics are textile materials which are made through weaving ,knitting, braiding and bonding of fibres. Weaving is described as inter-lacing of two distinct set of threads to form cloth, rug or other type of woven textile. The lengthways threads are known as the warp and the crossway threads are known as the weft.Quality plays a vital role in fabric manufacturing. The success of a weaving mill is significantly highlighted by its success in reducing fabric defects.Fabric inspection in offline is performed manually by skilled staff with a maximum accuracy of only 60%-75%. Automated fabric inspection would seem to offer a number of potential advantages, including improved safety, reduced labour costs, and the elimination of human error. Therefore, automated visual inspection is gaining increasing importance in weaving industry. This project proposes a automated fabric inspection system with benefits of low cost and high detection rate. Four types of faults are considered for analysis. Both normal and faulty images are processed and features are extracted using Gray Level Co-occurrence Matrix (GLCM).Further fuzzy rule based classsification is done.