Illumination compensation method using edge‐weakening guided image filter for face recognition

2015 ◽  
Vol 51 (19) ◽  
pp. 1495-1497 ◽  
Author(s):  
Chao Chen ◽  
Haibin Shen
Author(s):  
Yallamandaiah S. ◽  
Purnachand N.

<p>In the area of computer vision, face recognition is a challenging task because of the pose, facial expression, and illumination variations. The performance of face recognition systems reduces in an unconstrained environment. In this work, a new face recognition approach is proposed using a guided image filter, and a convolutional neural network (CNN). The guided image filter is a smoothing operator and performs well near the edges. Initially, the ViolaJones algorithm is used to detect the face region and then smoothened by a guided image filter. Later the proposed CNN is used to extract the features and recognize the faces. The experiments were performed on face databases like ORL, JAFFE, and YALE and attained a recognition rate of 98.33%, 99.53%, and 98.65% respectively. The experimental results show that the suggested face recognition method attains good results than some of the state-of-the-art techniques.</p>


2014 ◽  
Vol 39 (12) ◽  
pp. 2090-2099
Author(s):  
Lan LIN ◽  
Ge ZHAO ◽  
Yan-Dong TANG ◽  
Jian-Dong TIAN ◽  
Si-Yuan HE

2017 ◽  
Vol 77 (11) ◽  
pp. 13513-13530 ◽  
Author(s):  
Bo Jiang ◽  
Hongqi Meng ◽  
Jian Zhao ◽  
Xiaolei Ma ◽  
Siyu Jiang ◽  
...  

2017 ◽  
Vol 77 (3) ◽  
pp. 3125-3141 ◽  
Author(s):  
Bo Jiang ◽  
Hongqi Meng ◽  
Xiaolei Ma ◽  
Lin Wang ◽  
Yan Zhou ◽  
...  

2017 ◽  
Vol 66 (3) ◽  
pp. 139-151
Author(s):  
Khushboo Jain ◽  
Husanbir Singh Pannu ◽  
Kuldeep Singh ◽  
Avleen Malhi

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