Deep Slap Fingerprint Segmentation for Juveniles and Adults
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Abstract (arXiv)
Many fingerprint recognition systems capture four fingerprints in one image. In such systems, the fingerprint processing pipeline must first segment each four-fingerprint slap into individual fingerprints. Note that most of the current fingerprint segmentation algorithms have been designed and evaluated using only adult fingerprint datasets. In this work, we have developed a human-annotated in-house dataset of 15790 slaps of which 9084 are adult samples and 6706 are samples drawn from children from ages 4 to 12. Subsequently, the dataset is used to evaluate the matching performance of the NFSEG, a slap fingerprint segmentation system developed by NIST, on slaps from adults and juvenile subjects. Our results reveal the lower performance of NFSEG on slaps from juvenile subjects. Finally, we utilized our novel dataset to develop the Mask-RCNN based Clarkson Fingerprint Segmentation (CFSEG). Our matching results using the Verifinger fingerprint matcher indicate that CFSEG outperforms NFSEG for both adults and juvenile slaps. The CFSEG model is publicly available at urlhttps://github.com/keivanB/ClarksonFingerSegment
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 3 of its 17 references that are in the map. First posted on arXiv 6 Oct 2021.
Builds on
3 of 17 references.
References · 3
- 2015Deep Residual Learning for Image Recognitioncited by 51,809
- 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
- 2017Mask R-CNNcited by 7,259
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Citing papers per year: 2023: 3.
3 papers.