e-ISSN:0976-5166
p-ISSN:2231-3850


INDIAN JOURNAL OF COMPUTER SCIENCE AND ENGINEERING

Call for Papers

Apr 2019 - Volume 10, Issue 2
Deadline: 5 Apr 2019
Notification: 15 Apr 2019
Publication: 30 Apr 2019

June 2019 - Volume 10, Issue 3
Deadline: 5 June 2019
Notification: 15 June 2019
Publication: 30 June 2019

Indexed in

ABSTRACT

Title : RANK LEVEL FUSION USING FINGERPRINT AND IRIS BIOMETRICS
Authors : N. Radha, A. Kavitha
Keywords : Multimodal Biometric System; Rank Level Fusion; Logistic Regression; PCA (Principal Component Analysis); FLD (Fisher Linear Discriminant).
Issue Date : Dec 2011-Jan 2012
Abstract :
Authentication of users is an essential and difficult to achieve in all systems. Shared secrets like Personal Identification Numbers (PIN) or Passwords and key devices such as Smart cards are not presently sufficient in few situations. The biometric improves the capability to recognize the persons. A biometric identification system is an automatic recognition system that recognizes a person based on the physiological (e.g., fingerprints, face, retina, iris, ear) or behavioral (e.g., gait, signature, voice) characteristics. In many real-world applications, unimodal biometric systems often face has significant limitations due to sensitivity to noise, intra class variability, data quality, non-universality, and other factors. Multimodal biometric systems overcome some of these limitations. Multimodal biometric system provides more accuracy when compared to unimodal biometric system. The main goal of multimodal biometric system is to develop the security system for the areas that require high level of security. The proposed system focused on developing a multimodal biometrics system, which uses biometrics such as fingerprint and iris. Fusion of biometrics is performed by means of rank level fusion. The features from the biometrics are obtained by using the FLD (Fisher Linear Discriminant). The experimental result shows the performance of the proposed multimodal biometrics system. In this paper, the decision is made using rank level fusion and the ranks of individual persons are calculated using the Borda count, and Logistic regression approaches.
Page(s) : 917-923
ISSN : 0976-5166
Source : Vol. 2, No.6