GAYE: A face recognition system

Burcu Kepenekci; F. Boray Tek; Onur Çilingir; Ufuk Sakarya; Gozde Bozdagi Akar

doi:10.1117/12.528919

GAYE: A face recognition system

Burcu Kepenekci^*, F. Boray Tek, Onur Çilingir, Ufuk Sakarya, Gozde Bozdagi Akar

^*Bu çalışma için yazışmadan sorumlu yazar

Middle East Technical University

Araştırma sonucu: Dergiye katkı › Konferans makalesi › bilirkişi

1 Atıf (Scopus)

Özet

In this paper, a new face recognition system, GAYE, is presented. GAYE is a fully automatic system that detects and recognizes faces in cluttered scenes. The input of the system is any digitized image/image sequence that includes face/faces. The basic building blocks of the system are face detection, feature extraction and feature comparison. Face detection is based on skin color segmentation. For feature extraction, a novel approach is proposed that depends on the Gabor wavelet transform of the face image. By comparing facial feature vectors system finally makes a decision if the incoming person is recognized or not. Real time system tests show that GAYE achieves a recognition ratio over %90.

Orijinal dil	İngilizce
Sayfa (başlangıç-bitiş)	99-106
Sayfa sayısı	8
Dergi	Proceedings of SPIE - The International Society for Optical Engineering
Hacim	5298
DOI'lar	https://doi.org/10.1117/12.528919
Yayın durumu	Yayınlandı - 2004
Harici olarak yayınlandı	Evet
Etkinlik	Imaging Processing: Algorithms and Systems III - San Jose, CA, United States Süre: 19 Oca 2004 → 20 Oca 2004

Belgeye Erişim

10.1117/12.528919

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Alıntı Yap

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title = "GAYE: A face recognition system",

abstract = "In this paper, a new face recognition system, GAYE, is presented. GAYE is a fully automatic system that detects and recognizes faces in cluttered scenes. The input of the system is any digitized image/image sequence that includes face/faces. The basic building blocks of the system are face detection, feature extraction and feature comparison. Face detection is based on skin color segmentation. For feature extraction, a novel approach is proposed that depends on the Gabor wavelet transform of the face image. By comparing facial feature vectors system finally makes a decision if the incoming person is recognized or not. Real time system tests show that GAYE achieves a recognition ratio over %90.",

keywords = "Face detection, Face recognition, Feature extraction, Gabor wavelet transform",

author = "Burcu Kepenekci and {Boray Tek}, F. and Onur {\c C}ilingir and Ufuk Sakarya and Akar, {Gozde Bozdagi}",

year = "2004",

doi = "10.1117/12.528919",

language = "English",

volume = "5298",

pages = "99--106",

journal = "Proceedings of SPIE - The International Society for Optical Engineering",

issn = "0277-786X",

publisher = "SPIE",

note = "Imaging Processing: Algorithms and Systems III ; Conference date: 19-01-2004 Through 20-01-2004",

}

TY - JOUR

T1 - GAYE

T2 - Imaging Processing: Algorithms and Systems III

AU - Kepenekci, Burcu

AU - Boray Tek, F.

AU - Çilingir, Onur

AU - Sakarya, Ufuk

AU - Akar, Gozde Bozdagi

PY - 2004

Y1 - 2004

N2 - In this paper, a new face recognition system, GAYE, is presented. GAYE is a fully automatic system that detects and recognizes faces in cluttered scenes. The input of the system is any digitized image/image sequence that includes face/faces. The basic building blocks of the system are face detection, feature extraction and feature comparison. Face detection is based on skin color segmentation. For feature extraction, a novel approach is proposed that depends on the Gabor wavelet transform of the face image. By comparing facial feature vectors system finally makes a decision if the incoming person is recognized or not. Real time system tests show that GAYE achieves a recognition ratio over %90.

AB - In this paper, a new face recognition system, GAYE, is presented. GAYE is a fully automatic system that detects and recognizes faces in cluttered scenes. The input of the system is any digitized image/image sequence that includes face/faces. The basic building blocks of the system are face detection, feature extraction and feature comparison. Face detection is based on skin color segmentation. For feature extraction, a novel approach is proposed that depends on the Gabor wavelet transform of the face image. By comparing facial feature vectors system finally makes a decision if the incoming person is recognized or not. Real time system tests show that GAYE achieves a recognition ratio over %90.

KW - Face detection

KW - Face recognition

KW - Feature extraction

KW - Gabor wavelet transform

UR - http://www.scopus.com/inward/record.url?scp=8844249298&partnerID=8YFLogxK

U2 - 10.1117/12.528919

DO - 10.1117/12.528919

M3 - Conference article

AN - SCOPUS:8844249298

SN - 0277-786X

VL - 5298

SP - 99

EP - 106

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

Y2 - 19 January 2004 through 20 January 2004

ER -

GAYE: A face recognition system

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