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Multispectral analysis employed for palm related authentication uses light illumination in visible range (Red, Green, Blue) and Near Infrared (NIR) for capturing images, it combines the different information from different sources to enhances the performance of the system using a phenomenon termed as Biometric fusion. For this work, Multispectral Palmprint recognition was investigated using Principal Component Analysis (PCA) for images under different illuminations. Biometric fusion at image level was proposed where images captured under different illuminations were concatenated as triple (R,B,NIR and G,B,NIR) and a combination of four illuminations(R,G,B,NIR) accompanied by extraction of feature vectors from PCA space with incorporation of the K-Nearest Neighbour (K-NN) in the classification process. Experiments for the proposed approach were carried out on the PolyU Multispectral Database. The findings suggest that the concatenation demonstrated a good performance.The analysis should help guide one in the newly ongoing research field of Multispectral Imaging or anyone who may be considering designing a reliable and accurate Multispectral Palmprint Recognition system.
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Multispectral analysis employed for palm related authentication uses light illumination in visible range (Red, Green, Blue) and Near Infrared (NIR) for capturing images, it combines the different information from different sources to enhances the performance of the system using a phenomenon termed as Biometric fusion. For this work, Multispectral Palmprint recognition was investigated using Principal Component Analysis (PCA) for images under different illuminations. Biometric fusion at image level was proposed where images captured under different illuminations were concatenated as triple (R,B,NIR and G,B,NIR) and a combination of four illuminations(R,G,B,NIR) accompanied by extraction of feature vectors from PCA space with incorporation of the K-Nearest Neighbour (K-NN) in the classification process. Experiments for the proposed approach were carried out on the PolyU Multispectral Database. The findings suggest that the concatenation demonstrated a good performance.The analysis should help guide one in the newly ongoing research field of Multispectral Imaging or anyone who may be considering designing a reliable and accurate Multispectral Palmprint Recognition system.
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Multispectral Palmprint Recognition
Verlag:
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 3330089970
ISBN 13: 9783330089976
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Muhammad Abubakar SadiqAbubakar Sadiq Muhammad is a Lecturer from School of Technology,Kano State, Nigeria, He hadhis M.Sc Degree and B.Eng Degree in Computer Engineering from Mevlana University, Konya, Turkey and Bayero University, . Bestandsnummer des Verkäufers 385708112
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Multispectral Palmprint Recognition
Verlag:
LAP LAMBERT Academic Publishing Mär 2018, 2018
ISBN 10: 3330089970
ISBN 13: 9783330089976
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Taschenbuch. Zustand: Neu. Neuware -Multispectral analysis employed for palm related authentication uses light illumination in visible range (Red, Green, Blue) and Near Infrared (NIR) for capturing images, it combines the different information from different sources to enhances the performance of the system using a phenomenon termed as Biometric fusion. For this work, Multispectral Palmprint recognition was investigated using Principal Component Analysis (PCA) for images under different illuminations. Biometric fusion at image level was proposed where images captured under different illuminations were concatenated as triple (R,B,NIR and G,B,NIR) and a combination of four illuminations(R,G,B,NIR) accompanied by extraction of feature vectors from PCA space with incorporation of the K-Nearest Neighbour (K-NN) in the classification process. Experiments for the proposed approach were carried out on the PolyU Multispectral Database. The findings suggest that the concatenation demonstrated a good performance.The analysis should help guide one in the newly ongoing research field of Multispectral Imaging or anyone who may be considering designing a reliable and accurate Multispectral Palmprint Recognition system.Books on Demand GmbH, Überseering 33, 22297 Hamburg 60 pp. Englisch. Bestandsnummer des Verkäufers 9783330089976
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Multispectral Palmprint Recognition : An EigenBased Approach
Verlag:
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 3330089970
ISBN 13: 9783330089976
Neu
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Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Multispectral analysis employed for palm related authentication uses light illumination in visible range (Red, Green, Blue) and Near Infrared (NIR) for capturing images, it combines the different information from different sources to enhances the performance of the system using a phenomenon termed as Biometric fusion. For this work, Multispectral Palmprint recognition was investigated using Principal Component Analysis (PCA) for images under different illuminations. Biometric fusion at image level was proposed where images captured under different illuminations were concatenated as triple (R,B,NIR and G,B,NIR) and a combination of four illuminations(R,G,B,NIR) accompanied by extraction of feature vectors from PCA space with incorporation of the K-Nearest Neighbour (K-NN) in the classification process. Experiments for the proposed approach were carried out on the PolyU Multispectral Database. The findings suggest that the concatenation demonstrated a good performance.The analysis should help guide one in the newly ongoing research field of Multispectral Imaging or anyone who may be considering designing a reliable and accurate Multispectral Palmprint Recognition system. Bestandsnummer des Verkäufers 9783330089976
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Multispectral Palmprint Recognition
Verlag:
LAP LAMBERT Academic Publishing Mrz 2018, 2018
ISBN 10: 3330089970
ISBN 13: 9783330089976
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Multispectral analysis employed for palm related authentication uses light illumination in visible range (Red, Green, Blue) and Near Infrared (NIR) for capturing images, it combines the different information from different sources to enhances the performance of the system using a phenomenon termed as Biometric fusion. For this work, Multispectral Palmprint recognition was investigated using Principal Component Analysis (PCA) for images under different illuminations. Biometric fusion at image level was proposed where images captured under different illuminations were concatenated as triple (R,B,NIR and G,B,NIR) and a combination of four illuminations(R,G,B,NIR) accompanied by extraction of feature vectors from PCA space with incorporation of the K-Nearest Neighbour (K-NN) in the classification process. Experiments for the proposed approach were carried out on the PolyU Multispectral Database. The findings suggest that the concatenation demonstrated a good performance.The analysis should help guide one in the newly ongoing research field of Multispectral Imaging or anyone who may be considering designing a reliable and accurate Multispectral Palmprint Recognition system. 60 pp. Englisch. Bestandsnummer des Verkäufers 9783330089976
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Multispectral Palmprint Recognition: An EigenBased Approach
Verlag:
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 3330089970
ISBN 13: 9783330089976
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Paperback. Zustand: Brand New. 60 pages. 8.66x5.91x0.14 inches. In Stock. Bestandsnummer des Verkäufers 3330089970
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