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Fingerprint Matching with Localized Deep Representation
May 3, 2024, 4:59 a.m. | Yongjie Duan, Zhiyu Pan, Jianjiang Feng, Jie Zhou
cs.CV updates on arXiv.org arxiv.org
Abstract: Compared to minutia-based fingerprint representations, fixed-length representations are attractive due to simple and efficient matching. However, fixed-length fingerprint representations are limited in accuracy when matching fingerprints with different visible areas, which can occur due to different finger poses or acquisition methods. To address this issue, we propose a localized deep representation of fingerprint, named LDRF. By focusing on the discriminative characteristics within local regions, LDRF provides a more robust and accurate fixed-length representation for fingerprints …
abstract accuracy acquisition arxiv cs.ai cs.cv fingerprints however issue representation simple type
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