Texture classification using Gabor filters

Mahamadou Idrissa; Marc Acheroy

doi:10.1016/S0167-8655(02)00056-9

Texture classification using Gabor filters

Mahamadou Idrissa
, Marc Acheroy

Research output: Contribution to journal › Article › peer-review

157 Citations (Scopus)

Abstract

An unsupervised texture classification scheme is proposed in this paper. The texture features are based on the image local spectrum which is obtained by a bank of Gabor filters. The fuzzy clustering algorithm is used for unsupervised classification. In many applications, this algorithm depends on assumptions made about the number of subgroups present in the data. Therefore we discuss ideas behind cluster validity measures and propose a method for choosing the optimal number of clusters.

Original language	English
Pages (from-to)	1095-1102
Number of pages	8
Journal	Pattern Recognition Letters
Volume	23
Issue number	9
DOIs	https://doi.org/10.1016/S0167-8655(02)00056-9
Publication status	Published - Jul 2002

Keywords

Classification
Cluster validity
Fuzzy clustering
Gabor filters

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10.1016/S0167-8655(02)00056-9

Cite this

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title = "Texture classification using Gabor filters",

abstract = "An unsupervised texture classification scheme is proposed in this paper. The texture features are based on the image local spectrum which is obtained by a bank of Gabor filters. The fuzzy clustering algorithm is used for unsupervised classification. In many applications, this algorithm depends on assumptions made about the number of subgroups present in the data. Therefore we discuss ideas behind cluster validity measures and propose a method for choosing the optimal number of clusters.",

keywords = "Classification, Cluster validity, Fuzzy clustering, Gabor filters",

author = "Mahamadou Idrissa and Marc Acheroy",

year = "2002",

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AU - Idrissa, Mahamadou

AU - Acheroy, Marc

PY - 2002/7

Y1 - 2002/7

N2 - An unsupervised texture classification scheme is proposed in this paper. The texture features are based on the image local spectrum which is obtained by a bank of Gabor filters. The fuzzy clustering algorithm is used for unsupervised classification. In many applications, this algorithm depends on assumptions made about the number of subgroups present in the data. Therefore we discuss ideas behind cluster validity measures and propose a method for choosing the optimal number of clusters.

AB - An unsupervised texture classification scheme is proposed in this paper. The texture features are based on the image local spectrum which is obtained by a bank of Gabor filters. The fuzzy clustering algorithm is used for unsupervised classification. In many applications, this algorithm depends on assumptions made about the number of subgroups present in the data. Therefore we discuss ideas behind cluster validity measures and propose a method for choosing the optimal number of clusters.

KW - Classification

KW - Cluster validity

KW - Fuzzy clustering

KW - Gabor filters

UR - https://www.scopus.com/pages/publications/0036643398

U2 - 10.1016/S0167-8655(02)00056-9

DO - 10.1016/S0167-8655(02)00056-9

M3 - Article

AN - SCOPUS:0036643398

SN - 0167-8655

VL - 23

SP - 1095

EP - 1102

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

IS - 9

ER -

Texture classification using Gabor filters

Abstract

Keywords

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