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Inhaltsangabe
This book presents a novel approach for Face Recognition using ‘Vector Quantization’. Face Recognition is one of the popular biometric techniques used in today’s era. A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. Vector quantization is simple image compression technique. It is efficient for image coding because it reduces computational complexity. VQ compression is highly asymmetric in processing time: choosing an optimal codebook takes huge amounts of calculations, but decompression is lightning-fast—only one table lookup per vector. This makes VQ an excellent choice for face recognition. In this book four different VQ algorithms namely LBG, KPE, KMCG and KFCG are used to observe the efficiency of face recognition system. Efficiency is calculated in terms of recognition rate and computational complexity. It has been observed that KPE, KMCG and KFCG outperform LBG which is known as benchmark in vector quantization. Proposed techniques are compared with traditional DCT and Walsh transform also. It proves better than transform techniques.
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Reseña del editor
This book presents a novel approach for Face Recognition using ‘Vector Quantization’. Face Recognition is one of the popular biometric techniques used in today’s era. A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. Vector quantization is simple image compression technique. It is efficient for image coding because it reduces computational complexity. VQ compression is highly asymmetric in processing time: choosing an optimal codebook takes huge amounts of calculations, but decompression is lightning-fast—only one table lookup per vector. This makes VQ an excellent choice for face recognition. In this book four different VQ algorithms namely LBG, KPE, KMCG and KFCG are used to observe the efficiency of face recognition system. Efficiency is calculated in terms of recognition rate and computational complexity. It has been observed that KPE, KMCG and KFCG outperform LBG which is known as benchmark in vector quantization. Proposed techniques are compared with traditional DCT and Walsh transform also. It proves better than transform techniques.
Biografía del autor
Prachi Natu has received M.E. (Computer) degree from Mumbai University with distinction in 2010. She has 07 years of experience in teaching.Her areas of interest are Image Processing, Database Management Systems, Operating systems and Data Structure. She has 11 papers in International Conferences/journal to her credit.
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- VerlagLAP LAMBERT Academic Publishing
- Erscheinungsdatum2012
- ISBN 10 3659154318
- ISBN 13 9783659154317
- EinbandTapa blanda
- SpracheEnglisch
- Anzahl der Seiten96
- Kontakt zum HerstellerNicht verfügbar
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Face Recognition using Vector Quantization
Verlag:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659154318
ISBN 13: 9783659154317
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Natu PrachiPrachi Natu has received M.E. (Computer) degree from Mumbai University with distinction in 2010. She has 07 years of experience in teaching.Her areas of interest are Image Processing, Database Management Systems, Operating. Bestandsnummer des Verkäufers 5135450
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Face Recognition using Vector Quantization : A novel approach to Face Recognition
Verlag:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659154318
ISBN 13: 9783659154317
Neu
Taschenbuch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a novel approach for Face Recognition using 'Vector Quantization'. Face Recognition is one of the popular biometric techniques used in today's era. A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. Vector quantization is simple image compression technique. It is efficient for image coding because it reduces computational complexity. VQ compression is highly asymmetric in processing time: choosing an optimal codebook takes huge amounts of calculations, but decompression is lightning-fast-only one table lookup per vector. This makes VQ an excellent choice for face recognition. In this book four different VQ algorithms namely LBG, KPE, KMCG and KFCG are used to observe the efficiency of face recognition system. Efficiency is calculated in terms of recognition rate and computational complexity. It has been observed that KPE, KMCG and KFCG outperform LBG which is known as benchmark in vector quantization. Proposed techniques are compared with traditional DCT and Walsh transform also. It proves better than transform techniques. Bestandsnummer des Verkäufers 9783659154317
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Face Recognition using Vector Quantization
Verlag:
LAP LAMBERT Academic Publishing Jul 2012, 2012
ISBN 10: 3659154318
ISBN 13: 9783659154317
Neu
Taschenbuch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a novel approach for Face Recognition using 'Vector Quantization'. Face Recognition is one of the popular biometric techniques used in today's era. A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. Vector quantization is simple image compression technique. It is efficient for image coding because it reduces computational complexity. VQ compression is highly asymmetric in processing time: choosing an optimal codebook takes huge amounts of calculations, but decompression is lightning-fast-only one table lookup per vector. This makes VQ an excellent choice for face recognition. In this book four different VQ algorithms namely LBG, KPE, KMCG and KFCG are used to observe the efficiency of face recognition system. Efficiency is calculated in terms of recognition rate and computational complexity. It has been observed that KPE, KMCG and KFCG outperform LBG which is known as benchmark in vector quantization. Proposed techniques are compared with traditional DCT and Walsh transform also. It proves better than transform techniques. 96 pp. Englisch. Bestandsnummer des Verkäufers 9783659154317
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Face Recognition using Vector Quantization
Verlag:
LAP LAMBERT Academic Publishing Jul 2012, 2012
ISBN 10: 3659154318
ISBN 13: 9783659154317
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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Taschenbuch. Zustand: Neu. Neuware -This book presents a novel approach for Face Recognition using ¿Vector Quantization¿. Face Recognition is one of the popular biometric techniques used in today¿s era. A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. Vector quantization is simple image compression technique. It is efficient for image coding because it reduces computational complexity. VQ compression is highly asymmetric in processing time: choosing an optimal codebook takes huge amounts of calculations, but decompression is lightning-fast¿only one table lookup per vector. This makes VQ an excellent choice for face recognition. In this book four different VQ algorithms namely LBG, KPE, KMCG and KFCG are used to observe the efficiency of face recognition system. Efficiency is calculated in terms of recognition rate and computational complexity. It has been observed that KPE, KMCG and KFCG outperform LBG which is known as benchmark in vector quantization. Proposed techniques are compared with traditional DCT and Walsh transform also. It proves better than transform techniques.Books on Demand GmbH, Überseering 33, 22297 Hamburg 96 pp. Englisch. Bestandsnummer des Verkäufers 9783659154317
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Face Recognition using Vector Quantization: A novel approach to Face Recognition
Verlag:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659154318
ISBN 13: 9783659154317
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paperback. Zustand: Like New. Like New. book. Bestandsnummer des Verkäufers ERICA80036591543186
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