Hybrid Method for Face Description Using LBP and HOG

Authors

  • Dr.Kadhim M. M.AlMousawi
  • Azhaar Abd. Hassan 1Department of Computer Science, College of Education for Pure Science University of Thi-Qar, ThiQar-Iraq
  • Dr.Mustafa J. Hayawi

DOI:

https://doi.org/10.32792/jeps.v10i1.34

Keywords:

Face descriptor, hybrid, LBP, HOG

Abstract

Face recognition has become an important issue in our current life and it is a fundamental task for applications such as face tracking, red – eye removal, face recognition and face expression recognition.
In this paper we present a hybrid approach based on combination of local binary pattern (LBP)and Histogram of Oriented Gradient(HOG). LBP algorithms, which works with the shape and texture information are taken into consideration for representing the facial image. The hog algorithm of descriptor attributes is used to detect the object. It is computed using a dense grid of uniformly spaced cells and uses overlapping local contrast normalization for improved accuracy.
The ORL database was used to test each algorithm for a set of images. The efficiency of the LBP algorithm is evaluated by distinguishing a group of face images from 80%. The HOG algorithm achieved 90% classification accuracy obtained, while the hybrid method 94.25%.

References

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Published

2020-12-02

Issue

Vol. 10 No. 1 (2020)

Section

Articles

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