Back to Search Start Over

Moment-Based Features of Knitted Cotton Fabric Defect Classification by Artificial Neural Networks.

Authors :
Das, Subrata
Wahi, Amitabh
Kumar, S. Madhan
Mishra, Ravi Shankar
Sundaramurthy, S.
Source :
Journal of Natural Fibers; 2022, Vol. 19 Issue 4, p1498-1506, 9p
Publication Year :
2022

Abstract

The defect classification of knitted fabrics is a challenging area of research. Most of the defect detection works in India; Bangladesh is being carried by manually trained inspectors. The long working hours and the working environment at the company induces the fatigue, lack of concentration, and triteness to the workers due to this they may not able to detect the defects on the clothes after it is manufactured. To overcome this problem, a computer-aided defect detection system is being developed using digital image processing and artificial neural Network methods. The two types of artificial neural networks were applied to compare the results obtained. The networks were: a back propagation based feed forward neural network and the other was Levenberg–Marquardt (LM) algorithm based back propagation network. Experimental results predicted detection of a high degree of variety of fabric defects. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15440478
Volume :
19
Issue :
4
Database :
Complementary Index
Journal :
Journal of Natural Fibers
Publication Type :
Academic Journal
Accession number :
156415252
Full Text :
https://doi.org/10.1080/15440478.2020.1779900