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

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)