Dempster-Shafer theory based classifier fusion for improved fingerprint verification performance

• NCJ Number: 305865
• Author(s): Richa Singh ; Mayank Vatsa ; Afzel Noore ; Sanjay K. Singh
• Date Published: 2006
• Length: 9 pages
• Grant Number(s): 2003-RC-CX-K001
• Sponsoring Agency: National Institute of Justice (NIJ)
• Publication Format: Document (Online)
• Language: English
• Country: United States of America
• Note: In: Kalra, P.K., Peleg, S. (eds) Computer Vision, Graphics and Image Processing. Lecture Notes in Computer Science, vol 4338.

Annotation

This paper presents a classifier fusion algorithm based on Dempster Shafer theory that improves the performance of fingerprint verification.

Abstract

The proposed fusion algorithm combines decision induced match scores of minutiae, ridge, fingercode, and pore-based fingerprint verification algorithms and provides an improvement of at least 8.1% in the verification accuracy compared to the individual algorithms. Further, proposed fusion algorithm outperforms by at least 2.52% when compared with existing fusion algorithms. The authors also found that the use of Dempster’s rule of conditioning reduces the training time by approximately 191 seconds. (Published Abstract Provided)