• Title/Summary/Keyword: Karhuman-Loves Transform(KLT)

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A Face Recognition using the Hidden Markov Model and Karhuman Loevs Transform (Hidden Markov Model과 Karhuman Loevs Transform를 이용한 얼굴인식)

  • Kim, Do-Hyun;Hwang, Suen-Ki;Kang, Yong-Seok;Kim, Tae-Woo;Kim, Moon-Hwan;Bae, Cheol-Soo
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.4 no.1
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    • pp.3-8
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    • 2011

  • The work presented in this paper describes a Hidden Markov Model(HMM)-based framework for face recognition and face detection. The observation vectors used to characterize the statics of the HMM are obtained using the coefficients of the Karhuman-Loves Transform(KLT). The face recognition method presented in this paper reduces significantly the computational complexity of previous HMM-based face recognition systems, while slightly improving the recognition rate. In addition, the suggested method is more effective than the exiting ones in face extraction in terms of accuracy and others even under complex changes to the surroundings such as lighting.

  • https://doi.org/10.17661/jkiiect.2011.4.1.003 인용 PDF

Face Recognition Method Robust to Change in Lighting Condition (조명의 변화에 강건한 얼굴인식)

  • Nam, Kee-Hwan;Han, Jun-Hee;Park, Ho-Sik;Lee, Young-Sik;Jung, Yen-Gil;Ra, Sang-Dong;Bae, Cheol-Soo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.1
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    • pp.1137-1140
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    • 2005

  • The work presented in this paper describes a Hidden Markov Model(HMM)-based framework for face recognition and face detection. The observation vectors used to characterize the statics of the HMM are obtained using the coefficients of the Karhuman-Loves Transform(KLT). The face recognition method presented in this paper reduces significantly the computational complexity of previous HMM-based face recognition systems, while slightly improving the recognition rate. In addition, the suggested method is more effective than the exiting ones in face extraction in terms of accuracy and others even under complex changes to the surroundings such as lighting.

  • PDF