Comparison of Face Recognition Algorithms

Gunay M., Ensari T.

25th Signal Processing and Communications Applications Conference (SIU), Antalya, Turkey, 15 - 18 May 2017 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2017.7960469
  • City: Antalya
  • Country: Turkey
  • Istanbul University Affiliated: Yes

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.