TY  - JOUR
T1  - Effective Face Recognition Through Color Local Texture Features
AU - Arathy, V. AU - Babu, P. Srinivasa 
JO  - Asian Journal of Information Technology
VL  - 13
IS  - 3
SP  - 170
EP  - 174
PY  - 2014
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2014.170.174
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2014.170.174
KW  - Color face recognition
KW  -color local texture features
KW  -combination
KW  -principal component analysis
KW  -linear discriminant analysis
AB  - The new color local texture features that means Color Local 
  Gabor Wavelets (CLGWs) and Color Local Binary Pattern (CLBP), for the purpose 
  of Face Recognition (FR). This method is able to provide excellent recognition 
  rates for face images taken under severe variation in illumination as well as 
  for small (low) resolution face images. In addition, the feasibility of color 
  local texture features has been successfully demonstrated by making comparisons 
  with other state of the art color FR Methods. Color Local Texture Method do 
  not easy to recognize the face and if variation in face means do not get proper 
  results. Linear Discriminant Analysis (LDA) is commonly used technique for data 
  classification and dimensionality reduction. LDA approach overcomes the above 
  problem. The objective of LDA is to perform dimensionality reduction while preserving 
  as much of the class discriminatory information as possible. Linear discriminant 
  analysis is also known as Fisher’s 
  discriminant analysis and it searches for those vectors in the underlying space 
  that best discriminate among classes.
ER  -