Multimodal Face and Ear Recognition Using Feature Level and Score Level Fusion Approach

Title

Multimodal Face and Ear Recognition Using Feature Level and Score Level Fusion Approach

Creator

Resmi K.R.; Joseph A.; George B.

Description

Recent years have seen a significant increase in attention in multimodal biometric systems for personal identification especially in unconstrained environments. This paper presents a multimodal recognition system by combining feature level fusion of ear and profile face images. Multimodal biometric systems by combining face and ear can be used in an extensive range of applications because we can capture both the biometrics in a non-intrusive manner. Local texture feature descriptor, BSIF is used to extract discriminative features from biometric templates. Feature level and score level fusion is experimented to improve the performance of the system. Experimental results on different public datasets like GTAV, FEI, etc., show that the proposed method gives better performance in recognition results than individual modality. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

Source

Lecture Notes in Networks and Systems, Vol-843, pp. 279-288.

Date

2024-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

BSIF; Ear; Face; Feature level fusion; Multimodal biometrics; Score level fusion

Coverage

Resmi K.R., CHRIST (Deemed to be) University, Bengaluru, India; Joseph A., Santhigiri College, Kerala, Thodupuzha, India; George B., Santhigiri College, Kerala, Thodupuzha, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981998475-6

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-99-8476-3_22

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187658022&doi=10.1007%2f978-981-99-8476-3_22&partnerID=40&md5=1086c99d62c4ba03ba2396cd569ea3b9