Prachi Natu (7 results)

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  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2012

    3848491907 / 9783848491902

    • Softcover

    Seller: Mispah books, Redhill, SURRE, United KingdomMispah books

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    Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2012

    3659154318 / 9783659154317

    • Softcover

    Seller: Mispah books, Redhill, SURRE, United KingdomMispah books

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    paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

  • Language: English

    Published by LAP LAMBERT Academic Publishing Jul 2012, 2012

    3659154318 / 9783659154317

    • Softcover
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    Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condition: 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.

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2012

    3848491907 / 9783848491902

    • Softcover
    • Print on Demand

    Seller: moluna, Greven, Germanymoluna

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Natu ShachiMs. Shachi Natu has received M.E.(Computer) degree from Mumbai University with distinction in 2010. She has 07 years of experience in teaching. Currently working as Assistant Professor in department of I.T. at Thadomal Sha.

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2012

    3659154318 / 9783659154317

    • Softcover
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    Seller: moluna, Greven, Germanymoluna

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    Condition: 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.

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2012

    3659154318 / 9783659154317

    • Softcover
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    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Taschenbuch. Condition: 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.

  • Language: English

    Published by LAP LAMBERT Academic Publishing Jul 2012, 2012

    3659154318 / 9783659154317

    • Softcover
    • Print on Demand

    Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000

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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. 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.OmniScriptum SRL, Str. Armeneasca 28/1, office 1, 2012 Chisinau 96 pp. Englisch.