Face recognition under varying illumination using Mahalanobis self-organizing map

Saleh Aly, Naoyuki Tsuruta, Rin-Ichiro Taniguchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present an appearance-based method for face recognition and evaluate it with respect to robustness against illumination changes. Self-organizing map (SOM) used to transform the high dimensional face image into low dimensional topological space. However, the original learning algorithm of SOM uses Euclidean distance to measure similarity between input and codebook images, which is very sensitive to illumination changes. In this paper, we present Mahalanobis SOM, which uses Mahalanobis distance instead of the original Euclidean distance. The effectiveness of the proposed method is demonstrated by the experiments on Yale B and CMU-PIE face databases.

Original languageEnglish
Title of host publicationProceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08
Pages207-210
Number of pages4
Publication statusPublished - Dec 1 2008
Event13th International Symposium on Artificial Life and Robotics, AROB 13th'08 - Oita, Japan
Duration: Jan 31 2008Feb 2 2008

Publication series

NameProceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08

Other

Other13th International Symposium on Artificial Life and Robotics, AROB 13th'08
CountryJapan
CityOita
Period1/31/082/2/08

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

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  • Cite this

    Aly, S., Tsuruta, N., & Taniguchi, R-I. (2008). Face recognition under varying illumination using Mahalanobis self-organizing map. In Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08 (pp. 207-210). (Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08).