TY - JOUR
T1 - An adaptive illumination preprocessing method for face recognition
AU - Ren, Dong
AU - Chen, Junchao
AU - Zhang, Chong
AU - Liu, Zhongtu
AU - Liu, Xiaobo
AU - Zhou, Huan
PY - 2017/9/26
Y1 - 2017/9/26
N2 - Illumination variation is one of the most important challenges in face recognition, because changes to illumination conditions have a significant effect on performance. However, most illumination preprocessing methods apply the same level of processing to all facial images, without considering their unique illumination conditions. Therefore, the performances of existing preprocessing methods are limited when dealing with varying illumination conditions. In this paper, we propose an adaptive illumination preprocessing method for face recognition, which adaptively preprocesses each face image according to its illumination condition. The proposed method first uses the illumination quality index (IQI) to describe the illumination. Then, we create an adaptive parameter adjustment model for the illumination preprocessing method. Finally, the proposed model adjusts the parameters of the illumination preprocessing method based on the IQI of the facial image, and enhances the preprocessing effect. Our extensive simulation results show that the proposed method can effectively improve the performance of face recognition under varying illumination conditions, when compared with existing methods.
AB - Illumination variation is one of the most important challenges in face recognition, because changes to illumination conditions have a significant effect on performance. However, most illumination preprocessing methods apply the same level of processing to all facial images, without considering their unique illumination conditions. Therefore, the performances of existing preprocessing methods are limited when dealing with varying illumination conditions. In this paper, we propose an adaptive illumination preprocessing method for face recognition, which adaptively preprocesses each face image according to its illumination condition. The proposed method first uses the illumination quality index (IQI) to describe the illumination. Then, we create an adaptive parameter adjustment model for the illumination preprocessing method. Finally, the proposed model adjusts the parameters of the illumination preprocessing method based on the IQI of the facial image, and enhances the preprocessing effect. Our extensive simulation results show that the proposed method can effectively improve the performance of face recognition under varying illumination conditions, when compared with existing methods.
KW - Adaptive
KW - Face recognition
KW - Illumination normalization
KW - Illumination quality index
UR - http://www.scopus.com/inward/record.url?scp=85035105782&partnerID=8YFLogxK
U2 - 10.2316/Journal.206.2017.5.206-4969
DO - 10.2316/Journal.206.2017.5.206-4969
M3 - 文章
AN - SCOPUS:85035105782
SN - 0826-8185
VL - 32
SP - 509
EP - 516
JO - International Journal of Robotics and Automation
JF - International Journal of Robotics and Automation
IS - 5
ER -