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An Efficient Face Recognition Using Principle Component Analysis


Affiliations
1 Department of Electronics & Communication Engineering, School of Engineering, RK University, Rajkot, Gujarat, India
2 Department of Electronics & Communication Engineering, School of Engineering, RK University, Rajkot, Gujarat, India
     

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Face recognition systems have been grabbing high attention from commercial market point of view as well as pattern recognition field. It also stands high in researchers’ community. Face recognition have been fast growing, challenging and interesting area in real-time applications. A large number of face recognition algorithms have been developed from decades. The present paper refers to different face recognition approaches and primarily focuses on principal component analysis. This face recognition system detects the faces in a picture and these face images are then checked with training image dataset based on descriptive features. Descriptive features are used to characterize images. MATLAB Image processing toolbox is used for performing the image analysis.

Keywords

Eigenfaces, PCA, Face Recognition, Image Processing, Person Identification, Face Classification, MATLAB Image Processing Toolbox.
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  • An Efficient Face Recognition Using Principle Component Analysis

Abstract Views: 234  |  PDF Views: 3

Authors

N. M. Chhatrola
Department of Electronics & Communication Engineering, School of Engineering, RK University, Rajkot, Gujarat, India
P. A. Lathiya
Department of Electronics & Communication Engineering, School of Engineering, RK University, Rajkot, Gujarat, India

Abstract


Face recognition systems have been grabbing high attention from commercial market point of view as well as pattern recognition field. It also stands high in researchers’ community. Face recognition have been fast growing, challenging and interesting area in real-time applications. A large number of face recognition algorithms have been developed from decades. The present paper refers to different face recognition approaches and primarily focuses on principal component analysis. This face recognition system detects the faces in a picture and these face images are then checked with training image dataset based on descriptive features. Descriptive features are used to characterize images. MATLAB Image processing toolbox is used for performing the image analysis.

Keywords


Eigenfaces, PCA, Face Recognition, Image Processing, Person Identification, Face Classification, MATLAB Image Processing Toolbox.