Abstract
Illumination variation on images of faces is one of the most difficult problems in face recognition systems. The performance of a self-organizing map-based face recognition system is highly degraded when the illumination in test images differs from that of the training images. Illumination normalization is a way to solve this problem. Both global and local image enhancement methods are studied in this article. A local histogram equalization method strongly improves the recognition accuracy of the CMU-PIE face database.
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Aly, S., Sagheer, A., Tsuruta, N. et al. Face recognition across illumination. Artif Life Robotics 12, 33–37 (2008). https://doi.org/10.1007/s10015-007-0437-9
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DOI: https://doi.org/10.1007/s10015-007-0437-9