Comparison of Face Recognition Algorithms
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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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