Optimizing Fuzzy Rule Base for Illumination Compensation in Face Recognition using Genetic Algorithms
Journal Title: EMITTER International Journal of Engineering Technology - Year 2014, Vol 2, Issue 2
Abstract
Fuzzy rule optimization is a challenging step in the development of a fuzzy model. A simple two inputs fuzzy model may have thousands of combination of fuzzy rules when it deals with large number of input variations. Intuitively and trial‐error determination of fuzzy rule is very difficult. This paper addresses the problem of optimizing Fuzzy rule using Genetic Algorithm to compensate illumination effect in face recognition. Since uneven illumination contributes negative effects to the performance of face recognition, those effects must be compensated. We have developed a novel algorithm based on a reflectance model to compensate the effect of illumination for human face recognition. We build a pair of model from a single image and reason those models using Fuzzy. Fuzzy rule, then, is optimized using Genetic Algorithm. This approach spends less computation cost by still keeping a high performance. Based on the experimental result, we can show that our algorithm is feasible for recognizing desired person under variable lighting conditions with faster computation time.
Authors and Affiliations
Bima Sena Bayu Dewantara, Jun Miura
Keywords
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- EP ID EP170976
- DOI 10.24003/emitter.v2i2.27
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