Fingerprint recognition using neural network

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationNeural Networks for Signal Processing
PublisherPubl by IEEE
Pages226-235
ISBN (Print)780301188
Publication statusPublished - 1991

Conference

TitleProceedings of the 1991 Workshop on Neural Networks for Signal Processing - NNSP-91
CityPrinceton, NJ, USA
Period30 September - 2 October 1991

Abstract

This paper describes a neural network based approach for automated fingerprint recognition. Minutiae are extracted from the fingerprint image via a multilayer perceptron (MLP) classifier with one hidden layer. The backpropagation learning technique is used for its training. Selected features are represented in a special way such that they are simultaneously invariant under shift, rotation and scaling. Simulation results are obtained with good detection ratio and low failure rate. The proposed method is found to be reliable for system with a small set of fingerprint data.

Citation Format(s)

Fingerprint recognition using neural network. / Leung, W. F.; Leung, S. H.; Lau, W. H.; Luk, Andrew.

Neural Networks for Signal Processing. Publ by IEEE, 1991. p. 226-235.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review