Fingerprint Image Segmentation based on Oriented Pattern Analysis

Raimundo Claudio da Silva Vasconcelos, Helio Pedrini

2019

Abstract

Segmentation is a crucial task in automatic fingerprint identification systems. This paper describes a novel segmentation approach which takes into account the directional information inherent in fingerprint ridges. The method considers a directional operator to feed a k-means unsupervised clustering algorithm that labels the image in non-overlapping regions. Morphological operations are performed to fill holes and properly separate foreground from background. Experiments conducted on Fingerprint Verification Competition (FVC) datasets demonstrate that the proposed method, denoted as Oriented Pattern-based Segmentation (OPS), achieves competitive results when compared to other well-known available fingerprint segmentation approaches.

Paper Citation

in Harvard Style

Vasconcelos R. and Pedrini H. (2019). Fingerprint Image Segmentation based on Oriented Pattern Analysis. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP; ISBN 978-989-758-354-4, SciTePress, pages 405-412. DOI: 10.5220/0007409104050412

in Bibtex Style

@conference{visapp19,
author={Raimundo Claudio da Silva Vasconcelos and Helio Pedrini},
title={Fingerprint Image Segmentation based on Oriented Pattern Analysis},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP},
year={2019},
pages={405-412},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007409104050412},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP
TI - Fingerprint Image Segmentation based on Oriented Pattern Analysis
SN - 978-989-758-354-4
AU - Vasconcelos R.
AU - Pedrini H.
PY - 2019
SP - 405
EP - 412
DO - 10.5220/0007409104050412
PB - SciTePress