9783330089976 - Multispectral Palmprint Recognition: An EigenBased Approach di Muhammad, Abubakar Sadiq; Abdu, Fahad Jibrin; Muhammad, Abubakar Sani (6 risultati)

Paperback. Condizione: Brand New. 60 pages. 8.66x5.91x0.14 inches. In Stock.

Taschenbuch. Condizione: Neu. Multispectral Palmprint Recognition | An EigenBased Approach | Abubakar Sadiq Muhammad (u. a.) | Taschenbuch | 60 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9783330089976 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condizione: 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.

Condizione: 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, .

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.

Taschenbuch. Condizione: 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.