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

Paul, Liton Chandra; Suman, Abdulla Al

Softcover

ISBN 10: 3659461458 ISBN 13: 9783659461453

Publisher: LAP LAMBERT Academic Publishing, 2013

Synopsis

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.

About this title

About the Author

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

Edition details

• Publisher: LAP LAMBERT Academic Publishing
• Publication date: 2013
• Language: English
• ISBN 10: 3659461458
• ISBN 13: 9783659461453
• Binding: Paperback
• Number of pages: 80