Publication:
Comparison of Face Recognition Algorithms

Date
2017
Authors
Günay, Melike
Ensari, Tolga
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Publisher
IEEE, 345 E 47Th St, New York, Ny 10017 USA
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Abstract

in this study, we analyze the algorithms that is used for face recognition and make performance comparison of two algorithms. The methods that is analyzed are k-nearest neighbors, Naive Bayes, eigenfaces, principle component analysis (PCA) and k-means are implemented on ORL face dataset. As a result of the analysis, k-nearest neighbors algorithm and eigenfaces algoritm are the most successful and Naive Bayes has the worst performance result. Performance of k-nearest neighborhood which is the most succesfull one is decreasing from %94 to %91.5 after the princible component analysis. In addition, the difference increases to %7 for Naive Bayes algorithm.

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Keywords
Machine Learning , Face Recognition , Principle Component Analysis (PCA) , Naive Bayes , K-means , K-nearest Neighbor
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