In multimodal biometric technique strength of unimodal system biometrics are combined to increase recognition accuracy of the system. In this paper palm print and finger print biometrics are used to design robust recognition system. A feature of palm print are extracted with gray level co-occurrence based Harlick features and feature of finger print are extracted with minutiae based techniques. The proposed system is tested on publically available IIT Delhi Touch less Palm print database and FVC 2002 database for finger print. In this paper matching score level fusion technique with weighted sum rule based fusion is applied to fuse their individual score of palm print, finger print traits. The recognition accuracy is improved and it is found good as compared with recognition accuracy of individual traits. The multimodal system is evaluated on the basis of performance parameter, Accuracy 99.93 %, and Equal Error Rate (EER) is 0.0006.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.