HUMAN IDENTIFICATION BASED ON FACE RECOGNITION SYSTEM

Authors

  • Saba K. Naji Computer Engineering Department, Mustansiriyah University, Baghdad, Iraq Author
  • Muthana H. Hamad Computer Engineering Department, Mustansiriyah University, Baghdad, Iraq Author

DOI:

https://doi.org/10.31272/jeasd.25.1.7

Keywords:

face recognition, local binary pattern, local ternary pattern, Manhattan distance, Euclidean distance, Cosine distance

Abstract

Due to the great electronic development, which reinforced the need to define people's identities, different methods, and databases to identification people's identities have emerged. In this paper, we compare the results of two texture analysis methods: Local Binary Pattern (LBP) and Local Ternary Pattern (LTP). The comparison based on comparing the extracting facial texture features of 40 and 401 subjects taken from ORL and UFI databases respectively. As well, the comparison has taken in the account using three distance measurements such as; Manhattan Distance (MD), Euclidean Distance (ED), and Cosine Distance (CD). Where the maximum accuracy of the LBP method (99.23%) is obtained with a Manhattan and ORL database, while the LTP method attained (98.76%) using the same distance and database. While, the facial database of UFI shows low quality, which is satisfied 75.98% and 73.82% recognition rates using LBP and LTP respectively with Manhattan distance.

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Published

2021-01-01

Issue

Vol. 25 No. 1 (2021): Journal of Engineering and Sustainable Development

Section

Articles

License

Creative Commons License

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How to Cite

HUMAN IDENTIFICATION BASED ON FACE RECOGNITION SYSTEM. (2021). Journal of Engineering and Sustainable Development, 25(1), 80-91. https://doi.org/10.31272/jeasd.25.1.7