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Fusion Mechanism for Multimodal Biometric System-Palmprint and Fingerprint

Published: 10 August 2015 Publication History

Abstract

The major cause for increase in security breaches, fraud is the degraded quality of stored database. Thus, it is of great importance to make highly secure system in every field like military offices. The project developed for Multimodal Biometric System (MBS) based on image processing. The proposed MBS system is designed for applications like authentication of human being where a fingerprint images and palmprint for each individual used for training stage. The images are captured by using designed hardware; cameras used are Nikon Coolpix S01 10.1MP camera and Xpro night vision camera for palmprint and fingerprint resp. These captured images are preprocessed using Image enhancement techniques and Features are extracted by Gaussian kernel with edge detector, Gabor Filter and Principal Component analysis. Quality measures like length of principal lines, angle between them are also found for these above modalities. Quality base fusion as well as feature level fusion of extracted features are done. Later matching is done by using Canberra distance. This paper proposes unique own generated dataset of used modalities which improves system performance and accuracy up to the 90 to 95%.

References

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Norman Poh et al, "A Unified Framework for Biometric Expert Fusion Incorporating Quality Measures", IEEE Transactions on pattern analysis and machine intelligence, Vol. 34, No. 1, Jan. 2012 pp. 3--21.
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cover image ACM Other conferences
WCI '15: Proceedings of the Third International Symposium on Women in Computing and Informatics
August 2015
763 pages
ISBN:9781450333610
DOI:10.1145/2791405
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 August 2015

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  1. feature extraction
  2. fusion mechanism
  3. quality measures

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WCI '15

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WCI '15 Paper Acceptance Rate 98 of 452 submissions, 22%;
Overall Acceptance Rate 98 of 452 submissions, 22%

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