DocumentCode
3428459
Title
Defect detection and classification on web textile fabric using multiresolution decomposition and neural networks
Author
Karayiannis, Yorgos A. ; Stojanovic, Radovan ; Mitropoulos, Panagiotis ; Koulamas, Christos ; Stouraitis, Thanos ; Koubias, Stavros ; Papadopoulos, George
Author_Institution
VLSI Design Lab., Patras Univ., Greece
Volume
2
fYear
1999
fDate
5-8 Sep 1999
Firstpage
765
Abstract
In this paper a pilot system for defect detection and classification of web textile fabric in real-time is presented. The general hardware and software platform, developed for solving this problem, is presented while a powerful novel method for defect detection after multiresolution decomposition of the fabric images is proposed. This method gives good results in the detection of low contrast defects under real industrial conditions, where many types of noise are present. An artificial neural network, trained by a back-propagation algorithm, performs the defect classification in categories
Keywords
automatic optical inspection; backpropagation; image classification; industrial control; neural nets; production engineering computing; real-time systems; textile industry; wavelet transforms; artificial neural network; automated visual inspection system; backpropagation algorithm; defect classification; defect detection; fabric images; hardware platform; industrial conditions; low contrast defects; multiresolution decomposition; real-time operation; software platform; trained ANN; web textile fabric; Artificial neural networks; Cameras; Fabrics; Hardware; Humans; Inspection; Laboratories; Manufacturing industries; Real time systems; Textiles;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronics, Circuits and Systems, 1999. Proceedings of ICECS '99. The 6th IEEE International Conference on
Conference_Location
Pafos
Print_ISBN
0-7803-5682-9
Type
conf
DOI
10.1109/ICECS.1999.813221
Filename
813221
Link To Document