Bookcover of Face Recognition & Principal Component Analysis Method
Booktitle:

Face Recognition & Principal Component Analysis Method

Algorithm, Simulation & Discussion

LAP LAMBERT Academic Publishing (2013-09-25 )

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ISBN-13:

978-3-659-46145-3

ISBN-10:
3659461458
EAN:
9783659461453
Book language:
English
Blurb/Shorttext:
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.
Publishing house:
LAP LAMBERT Academic Publishing
Website:
https://www.lap-publishing.com/
By (author) :
Liton Chandra Paul, Abdulla al Suman
Number of pages:
80
Published on:
2013-09-25
Stock:
Available
Category:
Technology
Price:
39.90 €
Keywords:
Eigenvector, eigenvalue, PCA, euclidean distance., covariance., Face recognition

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