TY  - JOUR
T1  - Multimodal Biometric Authentication System Based Performance Scrutiny
AU - Manju, R. AU - Nargunam, A. Shajin AU - Rajendran, A. 
JO  - International Journal of Soft Computing
VL  - 9
IS  - 4
SP  - 246
EP  - 254
PY  - 2014
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2014.246.254
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2014.246.254
KW  - Biometric identification system
KW  -Fisher’s Linear Discriminant Methods (FLD)
KW  -Multibiometric System
KW  -Principal Component Analysis (PCA)
KW  -rank-level fusion
AB  - In many real-world applications, Unimodal Biometric Systems 
  often face significant limitations due to sensitivity to noise, intraclass variability, 
  data quality, non-universality and other factors. Multibiometric Systems seek 
  to alleviate some of these problems by providing multiple pieces of evidence 
  of the same identity. This study presents an effective fusion scheme that combines 
  information presented by multiple domain experts based on the Rank-Level Fusion 
  Integration Method. The developed Multimodal Biometric System possesses a number 
  of unique qualities, starting from utilizing principal component analysis and 
  Fisher’s Linear Discriminant 
  Methods for individual matchers (face, iris and fingerprint) identity authentication 
  and utilizing the Novel Rank-Level Fusion Method in order to consolidate the 
  results obtained from different biometric matchers.The results indicate that 
  fusion of individual modalities can improve the overall performance of the Biometric 
  System, even in the presence of low quality data.
ER  -