Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/24472
Title: A new intelligent fabric defect detection and classification system based on gabor filter and modified elman neural network
Authors: Zhang, YH
Yuen, CWM
Wong, WK 
Kan, CW 
Issue Date: 2010
Source: 2010 2nd International Conference on Advanced Computer Control (ICACC), 27-29 March 2010, Shenyang, p. 652-656
Abstract: In this paper, one fabric defect detection and classification system based on 2D Gabor wavelet transform and Elman neural network is introduced. In the proposed scheme, the texture features of the textile fabric are extracted by using an optimal 2D Gabor filter. A new modified Elman network is proposed to classify the type of fabric defects which have a proportional (P), integral (I) and derivative (D) properties. The proposed inspecting system in this study is more feasible and applicable in fabric defect detection and classification.
Keywords: Elman neural networ
Gabor filter
PID
Classification
Fabric defect detection
Publisher: IEEE
ISBN: 978-1-4244-5845-5
DOI: 10.1109/ICACC.2010.5486722
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

9
Last Week
0
Last month
Citations as of Feb 15, 2020

WEB OF SCIENCETM
Citations

4
Last Week
1
Last month
0
Citations as of Jan 19, 2020

Page view(s)

118
Last Week
6
Last month
Citations as of Feb 16, 2020

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.