Login | Register

An automated multimodal face recognition system based on fusion of face and ear

Title:

An automated multimodal face recognition system based on fusion of face and ear

Luciano, Lorenzo (2009) An automated multimodal face recognition system based on fusion of face and ear. Masters thesis, Concordia University.

[img]
Preview
Text (application/pdf)
MR63339.pdf - Accepted Version
5MB

Abstract

This thesis presents an automated system for the detection and recognition of humans using a multimodal approach. Face recognition is a biometric method which has in recent years become more relevant and needed. With heavy research, it is achieving respectable recognition rates and is becoming more mature as a technology. It is even being deployed in certain situations such as with passports and credit cards. Our multimodal biometric system uses both a person's face and ear to improve the recognition rate of individuals. By combining these two biometric systems we are able to achieve significantly improved recognition rates, as compared to using a unimodal biometric system. The system is totally automated, with a trained detection system for face and one for ear. We look at recognition rates for both face and ear, and then at combined recognition rates, and see that we have significant performance gains from the multimodal approach. We also discuss many existing methods of combining biometric input and the recognition rates that each achieves. Experimental results indicate that a multimodal biometric system has higher recognition rates than unimodal systems. This type of automated biometric recognition system can easily be used in installations requiring person identification such as person recognition in mugshots. It can also be used by security agencies and intelligence agencies requiring robust person identification systems.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (Masters)
Authors:Luciano, Lorenzo
Pagination:xii, 83 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M. Comp. Sc.
Program:Computer Science and Software Engineering
Date:2009
ID Code:976313
Deposited By: Concordia University Library
Deposited On:22 Jan 2013 16:23
Last Modified:18 Jan 2018 17:42
Related URLs:
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Research related to the current document (at the CORE website)
- Research related to the current document (at the CORE website)
Back to top Back to top