Textile industries that produce export quality fabrics are spread over southern part of India. One major aspect of an export fabric is the quality. Quality defines production and success rate of the industries. These textile industries which are working towards defect-less fabric production looks forward for an automated defect detection technique. This paper caters to the need of these textile industries. Any fabric defect detection process starts with identification and classification of the fabric defects. Fabric can be classified as natural or man-made fabric. Natural fabric is made from natural extracts from plants and animals whereas man-made fabric is made from chemical process. Fabric production is classified as knitted, woven and non-woven fabric. In this paper woven fabric defects identified and classified is reviewed. The woven fabric defects are listed as hole, slub, bad selvedge, float and many more. Here different methods for fabric defect identification and classification are analyzed. While doing so, it has been considered that their algorithms have been run in different systems with difficult configuration and different image quality. It is also considered that the database used by different authors are different.
Volume 11 | 04-Special Issue
Pages: 1197-1204