TY - GEN
T1 - Adaptive shadow removal algorithm for face images
AU - Zeng, Zhen
AU - Zhang, Rumin
AU - Chen, Jianwen
AU - Zeng, Liaoyuan
AU - Wang, Wenyi
AU - McGrath, Sean
PY - 2018
Y1 - 2018
N2 - ![CDATA[In the real world, illumination is an inevitable factor in face recognition. It has been proved that illumination variations are more significant than inherent variations between persons. This paper proposes an adaptive image processing method, which can not only suppress the effect of light in face recognition, but also remove shadow caused by illumination. In this paper, first, adaptive illumination preprocessing is performed to make the image have appropriate brightness. Then, the shadows boundaries of the image is extracted and binarized to obtain the shadow boundaries mask. Finally, the high-quality face image without shadows is reconstructed based on the mask of shadows boundaries and the face image after the illumination preprocessing. Experiments on the CMU-PIE dataset have shown that our method can achieve both good visual effects and a significant improvement in face recognition accuracy.]]
AB - ![CDATA[In the real world, illumination is an inevitable factor in face recognition. It has been proved that illumination variations are more significant than inherent variations between persons. This paper proposes an adaptive image processing method, which can not only suppress the effect of light in face recognition, but also remove shadow caused by illumination. In this paper, first, adaptive illumination preprocessing is performed to make the image have appropriate brightness. Then, the shadows boundaries of the image is extracted and binarized to obtain the shadow boundaries mask. Finally, the high-quality face image without shadows is reconstructed based on the mask of shadows boundaries and the face image after the illumination preprocessing. Experiments on the CMU-PIE dataset have shown that our method can achieve both good visual effects and a significant improvement in face recognition accuracy.]]
UR - https://hdl.handle.net/1959.7/uws:67498
U2 - 10.1109/ICSensT.2018.8603634
DO - 10.1109/ICSensT.2018.8603634
M3 - Conference Paper
SN - 9781538651476
SP - 227
EP - 231
BT - Proceedings of 2018 12th International Conference on Sensing Technology (ICST 2018), Limerick, Ireland, 4-6 December 2018
PB - IEEE
T2 - International Conference on Sensing Technology
Y2 - 2 December 2019
ER -