Pore-Based Ridge Reconstruction for Fingerprint Recognition
Abstract
The use of sweat pores in fingerprint recognition is becoming increasingly popular, mostly because of the wide availability of pores, which provides complementary information for matching distorted or incomplete images. In this work we present a fully automatic pore-based fingerprint recognition framework that combines both pores and ridges to measure the similarity of two images. To obtain the ridge structure, we propose a novel pore-based ridge reconstruction approach by considering a connect-the-dots strategy. To this end, Kruskal's minimum spanning tree algorithm is employed to connect consecutive pores and form a graph representing the ridge skeleton. We evaluate our framework on the PolyU HRF database, and the obtained results are favorably compared to previous results in the literature.
Cite
Text
Segundo and de Paula Lemes. "Pore-Based Ridge Reconstruction for Fingerprint Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2015. doi:10.1109/CVPRW.2015.7301328Markdown
[Segundo and de Paula Lemes. "Pore-Based Ridge Reconstruction for Fingerprint Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2015.](https://mlanthology.org/cvprw/2015/segundo2015cvprw-porebased/) doi:10.1109/CVPRW.2015.7301328BibTeX
@inproceedings{segundo2015cvprw-porebased,
title = {{Pore-Based Ridge Reconstruction for Fingerprint Recognition}},
author = {Segundo, Maurício Pamplona and de Paula Lemes, Rubisley},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2015},
pages = {128-133},
doi = {10.1109/CVPRW.2015.7301328},
url = {https://mlanthology.org/cvprw/2015/segundo2015cvprw-porebased/}
}