Identification of Human Facial Images using Visual Descriptors

Authors

  • Ayesha Aziz Prova  Computer Science and Engineering, Central Women’s University, Dhaka, Bangladesh
  • Md. Nazmul Hossain  Computer Science and Engineering, Jagannath University, Dhaka, Bangladesh

DOI:

https://doi.org/10.32628/IJSRSET218155

Keywords:

Face recognition, ReLBPH, instigator-threshold, Statistical histogram

Abstract

Discovering people using his face image now a vital research area for the researchers. This process is named face recognition. Every organization and not an organization even a county’s security system now ejected on a face image perception system. To evolve the face identifying complication the Local Binary Pattern Histogram (LBPH) is an unchanging way out method. But in the matter of illumination diversification, expression variation, and attitude deflection it gives less accurate than others. In our work, we have proposed a revised local binary pattern histogram (ReLBPH) for the way out of illumination diversification. We replace the gray form of LBP with a new threshold value, named instigator-threshold value instead of the threshold of the centric pixels of the sampled values of their neighbourhood sampling points. Using sub-blocks we extracted the features and then finally make the statistical histogram of these features. We use the FEI Standard database, DRFFI dataset and our constructed dataset for our experiment. We find maximum accuracy rate for the datasets.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2021-02-28

Issue

Volume 8, Issue 1, January-February-2021

Section

Research Articles

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How to Cite

[1]
Ayesha Aziz Prova, Md. Nazmul Hossain "Identification of Human Facial Images using Visual Descriptors" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 8, Issue 1, pp.229-238, January-February-2021. Available at doi : https://doi.org/10.32628/IJSRSET218155