COMPARATIVE ANALYSIS OF FACE RECOGNITION BASED ON SIGNIFICANT PRINCIPAL COMPONENTS OF PCA TECHNIQUE
Journal Title: International Journal of Computer Engineering & Technology (IJCET) - Year 2019, Vol 10, Issue 1
Abstract
Face recognition systems have been emerging as acceptable approaches for human authorization. Face recognition help in searching and classifying a face database and at a higher level help in identification of possible threats to security. In face recognition problem, the objective is to search a face in the reference face database that matches a given subject. The task of face recognition involves the extraction of feature vectors of the human face from the face image for differentiating it from other persons [6]. In this work, the comparative analysis is done based on the varying number of highly significant principal components (Eigenvectors) of PCA for face recognition. Experimental results show a small number of principal components of PCA are required for matching. PCA technique is a statistical technique, it reduces the dimension of the search space that best describes the images.
Authors and Affiliations
MANZOOR AHMAD LONE
Keywords
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- EP ID EP46512
- DOI 10.34218/IJCET.10.1.2019.011
- Views 246
- Downloads 0
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