• RAMYA N

The textile industry is mostly concerned with the design, manufacture and supply of fabrics. It is one of the main sources of revenue generated industry. The price of fabrics is severely affected by the defects of fabrics that represent a major risk to the textile industry. A very small percentage of defects are detected by the physical inspection even with highly trained inspectors. Although different types of fabric defects had been referenced in literatures, only a few patterned fabrics have been referenced. Researchers have been better result for minor defects. Automatic defect detection system will increase the defect detection percentage. It is economically profitable. An Artificial Neural Network is used as defect identification model. Digital image processing is the extracted option given as input to the neural network, it identifies the defects. This survey will be discussed about the existing methods for the major defects detection such as hole, broken end, thick bar, thin bar, multiple threading and knots.

Fabric defect detection; Inspection process; Automatic defect detection; Digital Image processing; Artificial Neural Network.

"SURVEY OF DEFECT DETECTION ON PATTERNED FABRICS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.42-50, June 2019, Available :http://www.jetir.org/papers/JETIR1906Y78.pdf

"SURVEY OF DEFECT DETECTION ON PATTERNED FABRICS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp42-50, June 2019, Available at : http://www.jetir.org/papers/JETIR1906Y78.pdf