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Efficient k-class approach for face recognition
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DOI：10.1016/j.compeleceng.2015.03.031.png)
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Abstract
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In this research work, a new k-class approach for efficient and accurate face recognition called kCAFRe is established. The kCAFRe system has three stages: preprocessing, training, and testing. In the training phase, four reference pictures (classes) are constructed for each person. During testing, the correlation coefficient (CC) is calculated between the picture under test and each of the reference pictures. For each person, one accredited class is chosen. Subsequently, the accredited class for the person with the highest CC is selected. Results were given for four image databases. A recognition ratio of 97% has been obtained for the Libor Spacek's set. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords:
Face detection
Face recognition
Recognition rate
Self-organizing-maps
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