- Natural-, Medical- , Computer Sciences, Technology
- Technology
- Face Recognition & Principal Component Analysis Method
- 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 )
eligible for voucher
- ISBN-13:
978-3-659-46145-3
- ISBN-10:
- 3659461458
- EAN:
- 9783659461453
- Book language:
- 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 at:
- 2013-09-25
- Stock:
- Available
- Category:
- Technology
- Price:
- 39.90 €
- Keywords:
- Eigenvector, eigenvalue, PCA, euclidean distance., covariance., Face recognition
