TY  - JOUR
T1  - Face Recognition Using Relationship Learning Based Super Resolution Algorithm
AU - Singh, C. Senthil AU - Manikandan, M. 
JO  - Asian Journal of Information Technology
VL  - 13
IS  - 3
SP  - 175
EP  - 181
PY  - 2014
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2014.175.181
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2014.175.181
KW  - Very Low Resolution (VLR)
KW  -Super Resolution (SR)
KW  -Relationship-Learning based SR (RLSR)
KW  -High Resolution (HR)
KW  -Low Resolution (LR)
AB  - The face recognition is an application which is used for identifying 
  or verifying a person from a digital image. The common problem that often occurs 
  while identifying the face from image is due to the low resolution in images 
  especially when it is captured from a long distance. In automated face recognition 
  system, this has always been a challeging problem. To overcome this problem, 
  an approach to learn relationship between the high resolution space and the 
  VLR image space for face is proposed. In this new approach the face recognition 
  applications under the VLR problem is designed for good visuality. To create 
  the Very Low Resolution (VLR) image corresponding to each of these High Resolution 
  (HR) images, the HR images are resized to 64x48 pixels. The Very Low Resolution 
  (VLR) of the face image is <16x12 pixels. The proposed system is implemented 
  in MATLAB. The performance of the proposed system is tested. The proposed system 
  is highly accurate and extremely fast in processing the image data. Experimental 
  results show that proposed method outperforms existing methods. The VLR face 
  recognition problem has been defined and discussed in this study. For good visual 
  quality applications, a new data constraint that measures the error in the HR 
  image space was developed and RLSR was proposed.
ER  -