Multimodal Biometrics Enhancement Recognition System based on Fusion of Fingerprint and PalmPrint: A Review

Multimodal Biometrics Enhancement Recognition System based on Fusion of Fingerprint and PalmPrint: A Review

Mouad. M.H.Ali

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A. T. Gaikwad

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Dr. Babasaheb Ambedkar Marathwada University

Multimodal Biometrics Enhancement Recognition System based on Fusion of Fingerprint and PalmPrint: A Review

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Abstract

This article is an overview of a current multimodal biometrics research based on fingerprint and palm-print. It explains the pervious study for each modal separately and its fusion technique with another biometric modal. The basic biometric system consists of four stages: firstly, the sensor which is used for enrolment & recognition the biometrics data. Secondly, the pre-processing stage which includes the enhancement and segmentation of Region-Of-Interest ROI. Thirdly, features extracted from the output of the pre-processing and each modal of biometrics having different type of features. Fourthly, the matching stage is to compare the acquired feature with the template in the database. Finally, the database which stores the features for the matching stags. Multimodal is being gathered of various types of biometrics objects from the same human. In this paper, the biometric system gives an explanation for each model. Also, the modalities of biometrics are discussed as well as focused on two different modalities : fingerprint and Palm-Print.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Mouad. M.H.Ali. 2016. \u201cMultimodal Biometrics Enhancement Recognition System based on Fusion of Fingerprint and PalmPrint: A Review\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 16 (GJCST Volume 16 Issue F2).

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GJCST Volume 16 Issue F2

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-F Classification C.2.0

Submission ReceivedDecember 10, 2015
Peer Review Double Blind
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Accepted January 1, 2016
Published January 15, 2016

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September 20, 2016

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Total Score: 102

Country: India

Subject: Global Journal of Computer Science and Technology - F: Graphics & Vision

Authors: Mouad. M.H.Ali, A. T. Gaikwad (PhD/Dr. count: 0)

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