Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/4570
Title: Minutiae Points Extraction Using Faster R-CNN
Authors: Baghel, Vivek Singh
Srivastava, Akhilesh Mohan
Prakash, Surya
Keywords: Intelligent computing;Biometric traits;Detection networks;Fingerprint authentication system;Fingerprint database;Fingerprint images;Minutiae points;Traditional techniques;Convolutional neural networks
Issue Date: 2021
Publisher: Springer Science and Business Media Deutschland GmbH
Citation: Baghel, V. S., Srivastava, A. M., Prakash, S., & Singh, S. (2021). Minutiae points extraction using faster R-CNN doi:10.1007/978-981-15-8610-1_1
Abstract: A fingerprint is an impression of the friction ridges of all parts of the finger and it is a widely used biometric trait. In a fingerprint authentication system, minutiae points are used as features to authenticate an individual. There are many traditional techniques which have been proposed to extract minutiae points from a fingerprint. However, efficiently locating minutiae points in a fingerprint image is still a challenging problem. In this paper, we propose a technique to locate and classify the minutiae points based on Faster R-CNN, which is a combination of region proposal network (RPN) and detection network. We use IIT Kanpur fingerprint database to evaluate the proposed technique and to show the performance. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
URI: https://doi.org/10.1007/978-981-15-8610-1_1
https://dspace.iiti.ac.in/handle/123456789/4570
ISBN: 9789811586095
ISSN: 2194-5357
Type of Material: Conference Paper
Appears in Collections:Department of Computer Science and Engineering

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