TY  - JOUR
T1  - Palm Print Texture Recognition Using Connected-Section Morphological Segmentation
AU - Kanchana, A. AU - Arumugam, S. 
JO  - Asian Journal of Information Technology
VL  - 13
IS  - 3
SP  - 119
EP  - 125
PY  - 2014
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2014.119.125
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2014.119.125
KW  - Biometrics
KW  -palm print recognition
KW  -morphological segmentation
KW  -connected section
KW  -texture variance
AB  - Biometric Recognition Method provides a greater recognition 
  rate, superior effectiveness and makes the user operating more comfortable. 
  Palm print recognition is considered the most feasible and consistent biometric 
  recognition technique remaining to its merits such as low cost, user sociability 
  with high speed and high accuracy. Advanced and fast correlation based feature 
  for palm print recognition based on modified correlation filter classifier with 
  spatial entities identifies more line features of the palm print very efficiently 
  and in a stochastic manner but fails to adapt the texture variance. To overcome 
  the above issue to implement a new technique termed Palm print Texture Recognition 
  using the Connected-section Morphological Segmentation (PTR-CMS) for effective 
  adaptation of texture variance and to remove the noise from palm print recognition. 
  PTR-CMS technique is to reliably segment the images to smaller regions from 
  the captured images. The proposed scheme is evaluated in terms of segmented 
  regional texture variance based on the partition size and average equal error 
  rate. Connected-section morphological segmentation (PTR-CMS) technique considers 
  the problem of which fails to provide texture variance. An analytical and empirical 
  result shows the lesser false acceptance rate with the efficient adaptation 
  of the texture variance of our proposed scheme.
ER  -