Face Recognition & Principal Component Analysis Method: Algorithm, Simulation & Discussion - Brossura

Paul, Liton Chandra; Suman, Abdulla Al

Brossura

ISBN 10: 3659461458 ISBN 13: 9783659461453

Casa editrice: LAP LAMBERT Academic Publishing, 2013

Riassunto

This book mainly addresses the building of face recognition system and Principal Component Analysis (PCA) method in details. PCA is a statistical approach used for reducing the number of variables in face recognition. In PCA, every image in the training set is represented as a linear combination of weighted eigenvectors called eigenfaces. These eigenvectors are obtained from covariance matrix of a training image set called as basis function. The weights are found out after selecting a set of most relevant Eigenfaces. Recognition is performed by projecting a test image onto the subspace spanned by the eigenfaces and then classification is done by measuring Euclidean distance. A number of experiments were done to evaluate the performance of the face recognition system. Here, I used a training database of students of ETE-07 series, RUET, Rajshahi-6204, Bangladesh.

Su questo libro

L'autore

Liton Chandra Paul (Nominated for President Gold Medal,1st Class 1st With Honors) received B.Sc in ETE from RUET, Rajshahi, Bangladesh.Currently, he is working as a lecturer of ETE department at PUST, Pabna, Bangladesh.He has more than 8 international journals & conference papers.He has also another book published by LAP LAMBERT Academic Publishing

Dettagli dell'edizione

• Editore: LAP LAMBERT Academic Publishing
• Data di pubblicazione: 2013
• Lingua: Inglese
• ISBN 10: 3659461458
• ISBN 13: 9783659461453
• Rilegatura: Copertina flessibile
• Numero di pagine: 80
• Contatto del produttore: non disponibile
• Persona responsabile: KreGa Onlinehandel GmbH; 4950000000000; info@krega-onlinehandel.de; ; Birkenweg 31; Brakel; 33034; Germania