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International Journal of Statistika and Mathematika, ISSN: 2277- 2790 E-ISSN: 2249-8605
Volume 10, Issue 1, May 2014 pp 08-11
Research Article
Performance Evaluation of Statistical Approaches of Face Recognition Techniques
Ruzal N. Surti, Anjana Rodrigues
Electronics Department, MPSTME, Mumbai, Maharashtra, INDIA.
Academic Editor: Dr. Dase R. K.
In today’s era of demanding technology of security and detection through images, Face recognition is one of the most relevant applications of image analysis and it has received substantial attention from both research communities and the market as face recognition. It’s a true challenge to build an automated system which equals human ability to recognize faces. This paper contains a survey on various statistical Techniques of face Recognition and evaluation of each. Images containing faces are normally represented as high-dimensional pixel arrays and often belong to a manifold of lower dimension. The dimensionality means the number of coordinates needed to specify a data point - of this data is too high. So the objective is to choose and apply the right statistical tool for extraction and analysis of the underlying manifold. One of the most relevant techniques is Principal Component Analysis (PCA).The main concern is regarding the memory needed to store the images for further process. PCA is the technique to reduce dimensionality of multi dimensional data by extracting principle components from it and however provides good statistical Analysis.
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