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Face Recognition for Surveillance Purpose: Using Orthogonal Transforms and Vector Quantization Techniques - Softcover

 
9783659351488: Face Recognition for Surveillance Purpose: Using Orthogonal Transforms and Vector Quantization Techniques

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This book is an attempt to unravel the problem of human face recognition. Face recognition is a biometric authentication method that has become more and more relevant in the recent years for the purpose of surveillance. Face recognition is a popular research area where there are different approaches studied in the literature. In this book face recognition problem is handled by applying Principal Component Analysis (PCA), Various Orthogonal transforms and different Vector Quantization (VQ) codebook generation techniques. The Eigen face method tries to find a lower dimensional space for the representation of the face images. The main drawback of PCA is scalability. As dataset changes the whole eigenspace distribution also changes. To avoid this difficulty various orthogonal transforms like DCT, DST, WHT, Slant, Wavelet Transform and newly proposed Kekre's Transform are applied on database. The concept of image energy compaction in low frequency coefficients is explored here.The VQ is considered to be a good data compression method. The key to VQ is the good codebook generation. Here the new technique for codebook generation is introduced as Kekre's Fast Code Book Generation (KFCG).

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Kamal Shah|Hemchandra Kekre
Published by LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659351482 ISBN 13: 9783659351488
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Shah KamalDr. Kamal Shah has received BE Electrical Engg. In 1996 from NIT-Surat and M.E. EXTC in 2005 from Mumbai University. She has completed her Ph.D in Engg. (Face Recognition) from NMIMS university in 2010. She has 15 years of . Seller Inventory # 385766477

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is an attempt to unravel the problem of human face recognition. Face recognition is a biometric authentication method that has become more and more relevant in the recent years for the purpose of surveillance. Face recognition is a popular research area where there are different approaches studied in the literature. In this book face recognition problem is handled by applying Principal Component Analysis (PCA), Various Orthogonal transforms and different Vector Quantization (VQ) codebook generation techniques. The Eigen face method tries to find a lower dimensional space for the representation of the face images. The main drawback of PCA is scalability. As dataset changes the whole eigenspace distribution also changes. To avoid this difficulty various orthogonal transforms like DCT, DST, WHT, Slant, Wavelet Transform and newly proposed Kekre's Transform are applied on database. The concept of image energy compaction in low frequency coefficients is explored here.The VQ is considered to be a good data compression method. The key to VQ is the good codebook generation. Here the new technique for codebook generation is introduced as Kekre's Fast Code Book Generation (KFCG). 288 pp. Englisch. Seller Inventory # 9783659351488

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Published by LAP LAMBERT Academic Publishing, 2014
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is an attempt to unravel the problem of human face recognition. Face recognition is a biometric authentication method that has become more and more relevant in the recent years for the purpose of surveillance. Face recognition is a popular research area where there are different approaches studied in the literature. In this book face recognition problem is handled by applying Principal Component Analysis (PCA), Various Orthogonal transforms and different Vector Quantization (VQ) codebook generation techniques. The Eigen face method tries to find a lower dimensional space for the representation of the face images. The main drawback of PCA is scalability. As dataset changes the whole eigenspace distribution also changes. To avoid this difficulty various orthogonal transforms like DCT, DST, WHT, Slant, Wavelet Transform and newly proposed Kekre's Transform are applied on database. The concept of image energy compaction in low frequency coefficients is explored here.The VQ is considered to be a good data compression method. The key to VQ is the good codebook generation. Here the new technique for codebook generation is introduced as Kekre's Fast Code Book Generation (KFCG). Seller Inventory # 9783659351488

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Taschenbuch. Condition: Neu. Neuware -This book is an attempt to unravel the problem of human face recognition. Face recognition is a biometric authentication method that has become more and more relevant in the recent years for the purpose of surveillance. Face recognition is a popular research area where there are different approaches studied in the literature. In this book face recognition problem is handled by applying Principal Component Analysis (PCA), Various Orthogonal transforms and different Vector Quantization (VQ) codebook generation techniques. The Eigen face method tries to find a lower dimensional space for the representation of the face images. The main drawback of PCA is scalability. As dataset changes the whole eigenspace distribution also changes. To avoid this difficulty various orthogonal transforms like DCT, DST, WHT, Slant, Wavelet Transform and newly proposed Kekre¿s Transform are applied on database. The concept of image energy compaction in low frequency coefficients is explored here.The VQ is considered to be a good data compression method. The key to VQ is the good codebook generation. Here the new technique for codebook generation is introduced as Kekre¿s Fast Code Book Generation (KFCG).Books on Demand GmbH, Überseering 33, 22297 Hamburg 288 pp. Englisch. Seller Inventory # 9783659351488

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