Implementation of a Transform-Minutiae Fusion-BasedModel for Fingerprint Recognition
Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
Hindawi
Abstract
Biometrics consists of scientific methods of using a person’s unique physiological or behavioral traits for electronic identification
and verification. The traits for biometric identification are fingerprint, voice, face, and palm print recognition. However, this study
considers fingerprint recognition for in-person identification since they are distinctive, reliable, and relatively easy to acquire.
Despite the many works done, the problem of accuracy still persists which perhaps can be attributed to the varying characteristic of
the acquisition devices. This study seeks to improve the issue recognition accuracy with the proposal of the fusion of a two
transform and minutiae models. In this study, a transform-minutiae fusion-based model for fingerprint recognition is proposed.
The first transform technique, thus wave atom transform, was used for data smoothing while the second transform, thus wavelet,
was used for feature extraction. These features were added to the minutiae features for person recognition. Evaluating the
proposed design on the FVC 2002 dataset showed a relatively better performance compared to existing methods with an accuracy
measure of 100% as to 96.67% and 98.55% of the existing methods
Description
Research Article