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Title: A new approach based in mean and standard deviation for authentication system of face
Authors: M. Fedias
D. Saigaa
Keywords: Eigenfaces, face authentication, statistical pattern recognition, feature extraction
Issue Date: 25-Nov-2014
Abstract: Face authentication is a significant problem in pattern recognition. The face is not rigid it can undergo a large variety of changes in illumination, facial expression and aging. Principal Component Analysis (PCA) is a typical and successful face based technique which considers face as global feature. In this paper, we developed a new simple method to extract the global feature vector based in the Mean and the Standard deviation (MS) of the image of face. Once the feature vector is extracted, the next stage consists of comparing it with the feature vector of face which is authenticated, and then we calculated the error rates in the two sets of evauation and test for the data base XM2VTS according to the protocol of Lausanne. The experimental results indicated that the extraction of image features is more efficient and faster using MS method than PCA. Copyright © 2010 Praise Worthy Prize S.r.l. - All rights reserved.
Appears in Collections:Publications Internationales

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