Human face recognition using weighted vote of Gabor magnitude filters

Iqbal Nouyed; M. Ashraful Amin; Bruce Poon; Hong Yan

Human face recognition using weighted vote of Gabor magnitude filters

Iqbal Nouyed, M. Ashraful Amin, Bruce Poon, Hong Yan

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

4 Citations (Scopus)

Abstract

Typically to extract the Gabor features from facial images, the magnitudes of the Gabor filter responses for different orientations and scales are used. We propose a weighted voting method using the 40 different Gabor magnitude representations which has shown 100% accuracy using two fold cross validation test where accuracy of conventional method was found to be 95% for 100 subjects using histogram intersection as similarity measure.

Original language	English
Title of host publication	7th International Conference on Information Technology and Application, ICITA 2011
Pages	36-40
Publication status	Published - 2011
Event	7th International Conference on Information Technology and Application, ICITA 2011 - Sydney, NSW, Australia Duration: 21 Nov 2011 → 24 Nov 2011

Conference

Conference	7th International Conference on Information Technology and Application, ICITA 2011
Place	Australia
City	Sydney, NSW
Period	21/11/11 → 24/11/11

Research Keywords

Gabor magnitude features
Gabor wavelets
Human face recognition
Local Gabor binary pattern

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@inproceedings{ad71842656f34a5091b6421a028d42e1,

title = "Human face recognition using weighted vote of Gabor magnitude filters",

abstract = "Typically to extract the Gabor features from facial images, the magnitudes of the Gabor filter responses for different orientations and scales are used. We propose a weighted voting method using the 40 different Gabor magnitude representations which has shown 100% accuracy using two fold cross validation test where accuracy of conventional method was found to be 95% for 100 subjects using histogram intersection as similarity measure.",

keywords = "Gabor magnitude features, Gabor wavelets, Human face recognition, Local Gabor binary pattern",

author = "Iqbal Nouyed and Amin, {M. Ashraful} and Bruce Poon and Hong Yan",

year = "2011",

language = "English",

isbn = "9780980326741",

pages = "36--40",

booktitle = "7th International Conference on Information Technology and Application, ICITA 2011",

note = "7th International Conference on Information Technology and Application, ICITA 2011 ; Conference date: 21-11-2011 Through 24-11-2011",

}

Human face recognition using weighted vote of Gabor magnitude filters. / Nouyed, Iqbal; Amin, M. Ashraful; Poon, Bruce et al.
7th International Conference on Information Technology and Application, ICITA 2011. 2011. p. 36-40.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Human face recognition using weighted vote of Gabor magnitude filters

AU - Nouyed, Iqbal

AU - Amin, M. Ashraful

AU - Poon, Bruce

AU - Yan, Hong

PY - 2011

Y1 - 2011

N2 - Typically to extract the Gabor features from facial images, the magnitudes of the Gabor filter responses for different orientations and scales are used. We propose a weighted voting method using the 40 different Gabor magnitude representations which has shown 100% accuracy using two fold cross validation test where accuracy of conventional method was found to be 95% for 100 subjects using histogram intersection as similarity measure.

AB - Typically to extract the Gabor features from facial images, the magnitudes of the Gabor filter responses for different orientations and scales are used. We propose a weighted voting method using the 40 different Gabor magnitude representations which has shown 100% accuracy using two fold cross validation test where accuracy of conventional method was found to be 95% for 100 subjects using histogram intersection as similarity measure.

KW - Gabor magnitude features

KW - Gabor wavelets

KW - Human face recognition

KW - Local Gabor binary pattern

UR - http://www.scopus.com/inward/record.url?scp=84868129317&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84868129317&origin=recordpage

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9780980326741

SP - 36

EP - 40

BT - 7th International Conference on Information Technology and Application, ICITA 2011

T2 - 7th International Conference on Information Technology and Application, ICITA 2011

Y2 - 21 November 2011 through 24 November 2011

ER -

Human face recognition using weighted vote of Gabor magnitude filters

Abstract

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Research Keywords

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