[1]YU Tuo,CHEN Ying.Face illumination compensation based on weighted edge-weakening guided image filter[J].CAAI Transactions on Intelligent Systems,2018,13(3):373-379.[doi:10.11992/tis.201612011]
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Face illumination compensation based on weighted edge-weakening guided image filter

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 13 Number of periods: 2018 3 Page number: 373-379 Column: 学术论文—机器感知与模式识别 Public date: 2018-05-05
Title:
Face illumination compensation based on weighted edge-weakening guided image filter
Author(s):
YU Tuo;  CHEN Ying
Key Laboratory of Advanced Process Control for Light Industry Ministry of Education, Jiangnan University, Wuxi 214122, China
Keywords:
face recognition; illumination compensation; illumination model; gaussian blur; guided image filter; ridge regression; loss function; self-quotient image
CLC:
TP391
DOI:
10.11992/tis.201612011
Abstract:
The variation of illumination is an important factor affecting the face recognition effect. Focusing on this problem, this study proposes a face illumination compensation based on a weighted edge-weakening guided image filter. First, a penalty item, whose edge details can be distinguished, was added into the loss function of the guided image filter. The penalty item was then weighted by a coefficient that was calculated by an inner-class mean face image of positive illumination samples. Finally, the filtered image was used as the smooth image in the self-quotient image to obtain the illumination compensation image. The experimental results showed that the proposed method can weaken the edge noise caused by the illumination in the smooth face area. Moreover, the face recognition rate can be improved using the illumination compensation image as the face recognition input, especially in the case of a large illumination variation.
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