Face Recognition using Neural Network & Principal Component Analysis
Pages : 2006-2009
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Abstract
The Human face image is contexture multidimensional point of perception version and by developing computational version for face recollection is rigid. The paper presents two methods for face identification, feature extraction is first method and classification is the second method. The classification is based on the Neural Network and feature is extraction is by Principal Component Analysis. The relevant information can be extracted by using the Eigenfaces, which are tenacious for face recognition. For face image identification the Eigenface image recognition the Eigen face perspective uses Principal Component Analysis (PCA) algorithm. The proposed system tested on 165 images from Yale face database. Test results gave a recognition rate above the 97%.
Keywords: Principal Component Analysis, Eigenface, Artificial Neural Network, MATLAB.
Article published in International Journal of Current Engineering and Technology, Vol.4,No.3 (June- 2014)