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Gender Identification from Facial Image using Compound Local Binary Pattern (CLBP

by Emam Hossain, Shayla Azad Bhuyan, Faisal Ahmed
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 100 - Number 3
Year of Publication: 2014
Authors: Emam Hossain, Shayla Azad Bhuyan, Faisal Ahmed
10.5120/17504-8052

Emam Hossain, Shayla Azad Bhuyan, Faisal Ahmed . Gender Identification from Facial Image using Compound Local Binary Pattern (CLBP. International Journal of Computer Applications. 100, 3 ( August 2014), 9-13. DOI=10.5120/17504-8052

@article{ 10.5120/17504-8052,
author = { Emam Hossain, Shayla Azad Bhuyan, Faisal Ahmed },
title = { Gender Identification from Facial Image using Compound Local Binary Pattern (CLBP },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 100 },
number = { 3 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 9-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume100/number3/17504-8052/ },
doi = { 10.5120/17504-8052 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:28:58.529509+05:30
%A Emam Hossain
%A Shayla Azad Bhuyan
%A Faisal Ahmed
%T Gender Identification from Facial Image using Compound Local Binary Pattern (CLBP
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 3
%P 9-13
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Automatic identification of male and female from facial image allows many useful applications in biometrics, surveillance, and human-computer interaction. This paper presents a robust face feature descriptor for gender classification from facial image. The proposed method is based on the compound local binary pattern (CLBP), an extension of the LBP texture operator. The CLBP operator exploits 2P bits to encode the information of a local neighborhood of P neighbors, where P bits are used to express the sign information and the other P bits are used to express the magnitude information of the differences between the center and the neighbor gray values. The performance of the proposed method has been evaluated using a large dataset comprising 1800 facial images collected from the FERET database. Extensive experiments with support vector machine classifier show the superiority of the CLBP feature descriptor against some well-known texture operators.

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Index Terms

Computer Science
Information Sciences

Keywords

Compound LBP (CLBP) Local texture Gender classification Support vector machine (SVM).

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