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A Hybrid Approach for Gender Classification of Web Images

by Muhammad Usman Khan, Hafiz Adnan Habib, Nasir Saleem
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 7
Year of Publication: 2012
Authors: Muhammad Usman Khan, Hafiz Adnan Habib, Nasir Saleem
10.5120/8577-2316

Muhammad Usman Khan, Hafiz Adnan Habib, Nasir Saleem . A Hybrid Approach for Gender Classification of Web Images. International Journal of Computer Applications. 54, 7 ( September 2012), 11-16. DOI=10.5120/8577-2316

@article{ 10.5120/8577-2316,
author = { Muhammad Usman Khan, Hafiz Adnan Habib, Nasir Saleem },
title = { A Hybrid Approach for Gender Classification of Web Images },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 7 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 11-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number7/8577-2316/ },
doi = { 10.5120/8577-2316 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:55:04.701551+05:30
%A Muhammad Usman Khan
%A Hafiz Adnan Habib
%A Nasir Saleem
%T A Hybrid Approach for Gender Classification of Web Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 7
%P 11-16
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent times, gender recognition of facial images has achieved lots of attraction. It can be useful in many places e. g. security, web searching, human computer interaction etc. In this paper, an approach containing both face detection and gender classification tasks has been proposed. In face detection part, Haar features have been chosen to present appearance features along with Ada-Boost technique to target strong and powerful features in cascaded form. For gender classification, Bayesian Classifier has been used where image is analyzed in blocks/patches form. The blocking technique is same as used in DCT approach. Experimental results have shown that proposed approach is effective and robust with changes in pose (some degree), expressions and illumination.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Haar Features Ada-Boost Bayesian Classifier DCT (Discrete Cosine Transform)

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