Multiscale Retinex Application to Analyze Face Recognition

Authors

  • Supriyanto Supriyanto Department of Computer and Informatics Engineering, Politeknik Negeri Bandung, Indonesia, Indonesia
  • Maisevli Harika Computer Vision and Artificial Intelligence Lab, Pukyong National University, Busan, South Korea, Korea, Republic of
  • Maya Sri Ramadiani Department of Computer and Informatics Engineering, Politeknik Negeri Bandung, Indonesia, Indonesia
  • Diena Rauda Ramdania Department of Informatics, UIN Sunan Gunung Djati Bandung, Indonesia, Indonesia

DOI:

https://doi.org/10.15575/join.v5i2.668

Keywords:

Face recognition, Lumination, Multiscale retinex, Principal component analysis, Variations

Abstract

The main challenge that facial recognition introduces is the difficulty of uneven lighting or dark tendencies. The image is poorly lit, which makes it difficult for the system to perform facial recognition. This study aims to normalize the lighting in the image using the Multiscale Retinex method. This method is applied to a face recognition system based on Principal Component Analysis to determine whether this method effectively improves images with uneven lighting. The results showed that the Multiscale Retinex approach to face recognition's correctness was better, from 40% to 76%. Multiscale Retinex has the advantage of dark facial image types because it produces a brighter image output.

Author Biography

Maisevli Harika, Computer Vision and Artificial Intelligence Lab, Pukyong National University, Busan, South Korea

Scopus Profile

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Published

2020-12-08

Issue

Vol. 5 No 2 (2020)

Section

Article

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