Welcome to the InfoSci Platform
Reference Hub10
Feature and Rank Level Fusion for Privacy Preserved Multi-Biometric System

Feature and Rank Level Fusion for Privacy Preserved Multi-Biometric System

Padma Polash Paul, Marina Gavrilova
Copyright: © 2015 |Volume: 7 |Issue: 1 |Pages: 17
ISSN: 1942-9045|EISSN: 1942-9037|EISBN13: 9781466677371|DOI: 10.4018/IJSSCI.2015010101
Cite Article Cite Article

MLA

Paul, Padma Polash, and Marina Gavrilova. "Feature and Rank Level Fusion for Privacy Preserved Multi-Biometric System." IJSSCI vol.7, no.1 2015: pp.1-17. http://doi.org/10.4018/IJSSCI.2015010101

APA

Paul, P. P. & Gavrilova, M. (2015). Feature and Rank Level Fusion for Privacy Preserved Multi-Biometric System. International Journal of Software Science and Computational Intelligence (IJSSCI), 7(1), 1-17. http://doi.org/10.4018/IJSSCI.2015010101

Chicago

Paul, Padma Polash, and Marina Gavrilova. "Feature and Rank Level Fusion for Privacy Preserved Multi-Biometric System," International Journal of Software Science and Computational Intelligence (IJSSCI) 7, no.1: 1-17. http://doi.org/10.4018/IJSSCI.2015010101

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Privacy protection in biometric system is a newly emerging biometric technology that can provide the protection against various attacks by intruders. In this paper, the authors have presented a multi-level of random projection method based on face and ear biometric traits. Privacy preserved templates are used in the proposed system. The main idea behind the privacy preserve computation is the random projection algorithm. Multiple random projection matrixes are used to generate multiple templates for biometric authentication. Newly introduced random fusion method is used in the proposed system; therefore, proposed method can provide better template security, privacy and feature quality. Multiple randomly fused templates are used for recognition purpose and finally decision fusion is applied to generate the final classification result. The proposed method works in a similar way human cognition for face recognition works, furthermore it preserve privacy and multimodality of the system.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.