Local Directional Amplitude Feature for Illumination Normalization with Application to Face Recognition
Face recognition under variant illumination conditions has been one of the major research topics in the development of face recognition systems. In this paper we analyze the strength and the weakness of different types of approaches, and design an illumination robust feature by combining the directional and amplitude information as an optimal solution to the problem. We first extract and process the direction and amplitude information of the pixel changes, and then fuse them into a comprehensive feature. We conducted our experiments on CMU-PIE database and Extended Yale B database, and all the results have shown the effectiveness of our approach.
KeywordsIllumination-invariant face recognition Direction and amplitude Local gravity Weberface
This work was supported in part by the National Natural Science Foundation of China under Grant 61673402, Grant 61273270, and Grant 60802069, in part by the Natural Science Foundation of Guangdong under Grant 2017A030311029, Grant 2016B010109002, Grant 2015B090912001, Grant 2016B010123005, and Grant 2017B090909005, in part by the Science and Technology Program of Guangzhou under Grant 201704020180 and Grant 201604020024, and in part by the Fundamental Research Funds for the Central Universities of China.
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