Palmprint Biometrics

Genovese, Angelo; Piuri, Vincenzo; Scotti, Fabio

doi:10.1007/978-3-319-10365-5_4

Cited by 5 publications

(1 citation statement)

References 170 publications

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“…all biometric modalities). For example, unlike the deep learning methods which can be used to analyze the image at several levels, the hand-crafted methods are applied at one level and due to its limits, it is not possible to access the depth of the image to extract the distinctive features even when there are very high-resolution biometric images [ 5 ]. However, deep learning is not always effective, especially in large databases, due to its need for powerful devices to overcome their main limitations, which are memory capacity and processor speed [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

An Effective Framework for Secure and Reliable Biometric Systems Based on Chaotic Maps

Laimeche

Meraoumia

Houam

et al. 2021

Pattern Recognition and Artificial Intelligence

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The last few years have plunged us at high speed into a new means of communication, namely the Internet, which has set a new trend for the next millennium. So, the rapid growth of online applications reflects the speed with which most countries can develop. An essential aspect of online communication is related to the trust of users and is a very necessary element to ensure the success of an online application. One of the main elements underlying this trust is the remote authentication of the user through its biometric features while of course protecting these features in different storage media. In this paper, we propose a new palmprint/palm-vein recognition framework based on a hand-craft image feature learning method is suggested. Furthermore, to increase the anti-spoof capability of the system, an effective biometric templates protection method based on chaotic systems was proposed. Experimental results have shown that high accuracy can be obtained with a very high level of template protection, which implies that the proposed cancelable biometric system can operate in highly secure applications.

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Section: Introductionmentioning

confidence: 99%