A multi-algorithm-based automatic person identification system

Md. Maruf Monwar; Marina Gavrilova

doi:10.1117/12.850669

19 April 2010 A multi-algorithm-based automatic person identification system

Md. Maruf Monwar, Marina Gavrilova

Proceedings Volume 7701, Visual Information Processing XIX; 770109 (2010) https://doi.org/10.1117/12.850669
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

Multimodal biometric is an emerging area of research that aims at increasing the reliability of biometric systems through utilizing more than one biometric in decision-making process. In this work, we develop a multi-algorithm based multimodal biometric system utilizing face and ear features and rank and decision fusion approach. We use multilayer perceptron network and fisherimage approaches for individual face and ear recognition. After face and ear recognition, we integrate the results of the two face matchers using rank level fusion approach. We experiment with highest rank method, Borda count method, logistic regression method and Markov chain method of rank level fusion approach. Due to the better recognition performance we employ Markov chain approach to combine face decisions. Similarly, we get combined ear decision. These two decisions are combined for final identification decision. We try with 'AND'/'OR' rule, majority voting rule and weighted majority voting rule of decision fusion approach. From the experiment results, we observed that weighted majority voting rule works better than any other decision fusion approaches and hence, we incorporate this fusion approach for the final identification decision. The final results indicate that using multi algorithm based can certainly improve the recognition performance of multibiometric systems.

Citation Download Citation

Md. Maruf Monwar and Marina Gavrilova "A multi-algorithm-based automatic person identification system", Proc. SPIE 7701, Visual Information Processing XIX, 770109 (19 April 2010); https://doi.org/10.1117/12.850669

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available