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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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