A new intelligent fabric defect detection and classification system based on Gabor filter and modified Elman neural network

Y. H. Zhang; C. W.M. Yuen; Wai Keung Wong

doi:10.1109/ICACC.2010.5486722

A new intelligent fabric defect detection and classification system based on Gabor filter and modified Elman neural network

Y. H. Zhang, C. W.M. Yuen, Wai Keung Wong

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

10 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings - 2nd IEEE International Conference on Advanced Computer Control, ICACC 2010
Pages	652-656
Number of pages	5
Volume	2
DOIs	https://doi.org/10.1109/ICACC.2010.5486722
Publication status	Published - 21 Oct 2010
Event	2010 IEEE International Conference on Advanced Computer Control, ICACC 2010 - Duration: 27 Mar 2010 → 29 Mar 2010

Conference

Conference	2010 IEEE International Conference on Advanced Computer Control, ICACC 2010
Period	27/03/10 → 29/03/10

Keywords

Classification
Elman neural networ
Fabric defect detection
Gabor filter
PID

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

More information

10.1109/ICACC.2010.5486722

Cite this

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title = "A new intelligent fabric defect detection and classification system based on Gabor filter and modified Elman neural network",

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 = "Classification, Elman neural networ, Fabric defect detection, Gabor filter, PID",

author = "Zhang, {Y. H.} and Yuen, {C. W.M.} and Wong, {Wai Keung}",

year = "2010",

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doi = "10.1109/ICACC.2010.5486722",

language = "English",

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volume = "2",

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Zhang, YH, Yuen, CWM & Wong, WK 2010, A new intelligent fabric defect detection and classification system based on Gabor filter and modified Elman neural network. in Proceedings - 2nd IEEE International Conference on Advanced Computer Control, ICACC 2010. vol. 2, 5486722, pp. 652-656, 2010 IEEE International Conference on Advanced Computer Control, ICACC 2010, 27/03/10. https://doi.org/10.1109/ICACC.2010.5486722

A new intelligent fabric defect detection and classification system based on Gabor filter and modified Elman neural network. / Zhang, Y. H.; Yuen, C. W.M.; Wong, Wai Keung.

Proceedings - 2nd IEEE International Conference on Advanced Computer Control, ICACC 2010. Vol. 2 2010. p. 652-656 5486722.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AU - Wong, Wai Keung

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Y1 - 2010/10/21

N2 - 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.

AB - 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.

KW - Classification

KW - Elman neural networ

KW - Fabric defect detection

KW - Gabor filter

KW - PID

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DO - 10.1109/ICACC.2010.5486722

M3 - Conference article published in proceeding or book

SN - 9781424458462

VL - 2

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EP - 656

BT - Proceedings - 2nd IEEE International Conference on Advanced Computer Control, ICACC 2010

T2 - 2010 IEEE International Conference on Advanced Computer Control, ICACC 2010

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A new intelligent fabric defect detection and classification system based on Gabor filter and modified Elman neural network

Abstract

Conference

Keywords

ASJC Scopus subject areas

More information

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