Although progress in face recognition is encouraging, the accuracy rate of face recognition remains to be
increased. Since the face image quality has a positive influence on face recognition accuracy, the image enhancement
methods are popular in face recognition. Most current image enhancement methods aim at improving visual
appearance, but cannot improve recognition accuracy remarkably. In this paper, a feature evaluation operator
is designed to overcome this problem. The operator selects patches with the best quality, and then face image
is reconstructed with the selected patches. The proposed algorithm is tested on two different face recognition
applications. Accuracy is raised after enhancement, and the result proves that the proposed algorithm is effective.
WANG Yunfei (王云飞), DING Hui (丁辉), SHANG Yuanyuan (尚媛园), SHAO Zhuhong (邵珠宏), FU Xiaoyan (付小雁)
. Improved Anchored Neighborhood Regression Enhancement for Face Recognition[J]. Journal of Shanghai Jiaotong University(Science), 2018
, 23(5)
: 600
-606
.
DOI: 10.1007/s12204-018-1989-7
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