Face Recognition & Principal Component Analysis Method

Name: Face Recognition & Principal Component Analysis Method
Brand: LAP Lambert Academic Publishing
SKU: 9783659461453
Price: 34.59 EUR
Availability: InStock

Algorithm, Simulation & Discussion

Autor: Liton Chandra Paul, Abdulla al Suman

Jazyk:

Väzba: Brožovaná

Vydavateľ: LAP Lambert Academic Publishing

Dostupnosť: Skladom u dodávateľa

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34.59 €

This book mainly addresses the building of face recognition system and Principal Component Analysis...

Informácie o knihe

Autor

Liton Chandra Paul, Abdulla al Suman

Jazyk

Angličtina

Väzba

Kniha - Brožovaná

Vydalo

2013

Stránok

EAN

9783659461453

Enbook ID

02201775

Vydavateľ

LAP Lambert Academic Publishing

Hmotnosť

137

Rozmery

150 x 220 x 5

Kompletný popis

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.

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Face Recognition & Principal Component Analysis Method

Algorithm, Simulation & Discussion

Informácie o knihe

Kompletný popis

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