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Hyperspectral Face Recognition: Using Multidimensional Clustering on Hyperspectral Face Images - Softcover
Synopsis
In this book the hyperspectral face recognition system is explored in the context of digital signal & image processing techniques. Hyperspectral images contain a wealth of data, but interpreting them requires an understanding of exactly what properties of human face we are trying to measure, and how they relate to the measurements actually made by the hyperspectral sensor. With the availability of hyperspectral face data it is possible to build systems on this. Main focus current research is to use hyperspectral face images in order to recognition the face. Hyperspectral face images with 33 band are used for generation of Vector Quantization based feature vector extraction process. These images are grouped into eleven sub-bands of three images each. Algorithms like Kekre’s Fast Codebook Generation (KFCG) Algorithm and Kekre’s Median Codebook Generation (KMCG) Algorithm are used to generate codebooks for each sub-band and then store into feature vector database. This feature vector set is used for identification of the person. . K-Nearest Neighborhood classifier (K-NN) is used and performance is evaluated, metrics such as EER, SPI, PI are used for benchmarking.
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About the Author
Dr. V. A. Bharadi has received B.E. Electronics Engg.in 2002 & M. E. Electronics & Telecomm in 2007 fromMumbai University. He has completed Ph.D. inEngineering (Biometrics Authentication Systems)fromNMIMS University in 2011. He has worked Over 10years as a faculty of Electronics & IT Engg. He haspublished 100+ National & International papers
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Hyperspectral Face Recognition
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LAP LAMBERT Academic Publishing Apr 2014, 2014
ISBN 10: 3659363529
ISBN 13: 9783659363528
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book the hyperspectral face recognition system is explored in the context of digital signal & image processing techniques. Hyperspectral images contain a wealth of data, but interpreting them requires an understanding of exactly what properties of human face we are trying to measure, and how they relate to the measurements actually made by the hyperspectral sensor. With the availability of hyperspectral face data it is possible to build systems on this. Main focus current research is to use hyperspectral face images in order to recognition the face. Hyperspectral face images with 33 band are used for generation of Vector Quantization based feature vector extraction process. These images are grouped into eleven sub-bands of three images each. Algorithms like Kekre's Fast Codebook Generation (KFCG) Algorithm and Kekre's Median Codebook Generation (KMCG) Algorithm are used to generate cod Elektronisches Buch for each sub-band and then store into feature vector database. This feature vector set is used for identification of the person. . K-Nearest Neighborhood classifier (K-NN) is used and performance is evaluated, metrics such as EER, SPI, PI are used for benchmarking. 100 pp. Englisch. Seller Inventory # 9783659363528
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Hyperspectral Face Recognition
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bharadi VinayakDr. V. A. Bharadi has received B.E. Electronics Engg.in 2002 & M. E. Electronics & Telecomm in 2007 fromMumbai University. He has completed Ph.D. inEngineering (Biometrics Authentication Systems)fromNMIMS University i. Seller Inventory # 5151232
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Hyperspectral Face Recognition : Using Multidimensional Clustering on Hyperspectral Face Images
Published by
LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659363529
ISBN 13: 9783659363528
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book the hyperspectral face recognition system is explored in the context of digital signal & image processing techniques. Hyperspectral images contain a wealth of data, but interpreting them requires an understanding of exactly what properties of human face we are trying to measure, and how they relate to the measurements actually made by the hyperspectral sensor. With the availability of hyperspectral face data it is possible to build systems on this. Main focus current research is to use hyperspectral face images in order to recognition the face. Hyperspectral face images with 33 band are used for generation of Vector Quantization based feature vector extraction process. These images are grouped into eleven sub-bands of three images each. Algorithms like Kekre's Fast Codebook Generation (KFCG) Algorithm and Kekre's Median Codebook Generation (KMCG) Algorithm are used to generate cod Elektronisches Buch for each sub-band and then store into feature vector database. This feature vector set is used for identification of the person. . K-Nearest Neighborhood classifier (K-NN) is used and performance is evaluated, metrics such as EER, SPI, PI are used for benchmarking. Seller Inventory # 9783659363528
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Hyperspectral Face Recognition
Published by
LAP LAMBERT Academic Publishing Apr 2014, 2014
ISBN 10: 3659363529
ISBN 13: 9783659363528
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book the hyperspectral face recognition system is explored in the context of digital signal & image processing techniques. Hyperspectral images contain a wealth of data, but interpreting them requires an understanding of exactly what properties of human face we are trying to measure, and how they relate to the measurements actually made by the hyperspectral sensor. With the availability of hyperspectral face data it is possible to build systems on this. Main focus current research is to use hyperspectral face images in order to recognition the face. Hyperspectral face images with 33 band are used for generation of Vector Quantization based feature vector extraction process. These images are grouped into eleven sub-bands of three images each. Algorithms like Kekre's Fast Codebook Generation (KFCG) Algorithm and Kekre's Median Codebook Generation (KMCG) Algorithm are used to generate cod Elektronisches Buch for each sub-band and then store into feature vector database. This feature vector set is used for identification of the person. . K-Nearest Neighborhood classifier (K-NN) is used and performance is evaluated, metrics such as EER, SPI, PI are used for benchmarking.OmniScriptum SRL, Str. Armeneasca 28/1, office 1, 2012 Chisinau 100 pp. Englisch. Seller Inventory # 9783659363528
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Hyperspectral Face Recognition | Using Multidimensional Clustering on Hyperspectral Face Images
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ISBN 13: 9783659363528
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Taschenbuch. Condition: Neu. Hyperspectral Face Recognition | Using Multidimensional Clustering on Hyperspectral Face Images | Vinayak Bharadi (u. a.) | Taschenbuch | 100 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659363528 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 105296551
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