An Effective Face Recognition in Various Lighting Conditions Using LBP/LTP Techniques
DOI:
https://doi.org/10.51983/ajcst-2012.1.1.1674Keywords:
Face recognition, illumination invariance, preprocessing, kernel principal components analysis, local patterns, visual featuresAbstract
Making recognition is more reliable under uncontrolled lighting conditions is one of the most important challenges for practical face recognition systems. We tackle this by combining following methods. The first step is simple and efficient preprocessing chain. The preprocessing is used to avoid the unwanted illumination effects such as Non-uniform illumination, Shadowing & highlights, aliasing, blurring and noise. Second step includes local binary pattern (LBP) and local ternary pattern methods (LTP). LBP is possible to describe the texture and shape of a digital image. LTP is a generalization of the local binary pattern (LBP). Local texture descriptor that is more discriminant and less sensitive to noise in uniform regions. The final step is used to improve robustness by adding two complementary sources Gabor wavelets and LBP showing that the combination is considerably more accurate than either feature set alone.
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