Call For Paper Volume:4 Issue:8 Aug'2017 |

A COMPARATIVE ANALYSIS OF LINEAR DISCRIMINANT, PRINCIPAL COMPONENT AND EVOLUTIONARY PURSUIT FOR RECOGNITION OF HUMAN FACES

Publication Date : 07/04/2016



Author(s) :

M.Vinodhini , C.Aishwarya , K.Jainul Safrina , K.Ramya.


Volume/Issue :
Volume 3
,
Issue 3
(04 - 2016)



Abstract :

Face Recognition system is a computer based security system that can automatically detect and identify human faces. It is used to provide government facilities, in access control systems and detecting criminals. It is also used for video surveillance system in both on-line and off-line. Early face recognition algorithm uses simple geometric models and now the recognition process has matured into mathematical representation and matching process. The algorithms of face recognition system are Principal component analysis (PCA), Linear discriminant analysis (LDA), and Evolutionary pursuit (EP). In Principal component analysis, input image is compared with the face images which is divided into small sets of character feature through distance measuring methods. Linear discriminant analysis is used for recognizing human subject. This allows objective evaluation of the significance of visual information in different parts. Evolutionary pursuit implements strategies characteristics of genetic algorithm for searching the space of possible solutions to determine the optimal basis. The original data is projected into lower dimension whitened PCA space. In this paper a comparative study of different human faces is analyzed and implemented using the above three face recognition algorithm.


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A COMPARATIVE ANALYSIS OF LINEAR DISCRIMINANT, PRINCIPAL COMPONENT AND EVOLUTIONARY PURSUIT FOR RECOGNITION OF HUMAN FACES

March 23, 2016