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dc.contributor.authorSalazar-Jurado, Edwin
dc.contributor.authorHernández-García, Ruber
dc.contributor.authorVilches-Ponce, Karina
dc.contributor.authorBarrientos, Ricardo
dc.contributor.authorMora, Marco
dc.contributor.authorGaurav, Jaswal
dc.date.accessioned2022-12-26T12:58:15Z
dc.date.available2022-12-26T12:58:15Z
dc.date.issued2023
dc.identifier.urihttp://repositorio.ucm.cl/handle/ucm/4252
dc.description.abstractWith the recent success of computer vision and deep learning, remarkable progress has been achieved on automatic personal recognition using vein biometrics. However, collecting large-scale real-world training data for palm vein recognition has turned out to be challenging, mainly due to the noise and irregular variations included at the time of acquisition. Meanwhile, existing palm vein recognition datasets are usually collected under near-infrared light, lacking detailed annotations on attributes (e.g., pose), so the influences of different attributes on vein recognition have been poorly investigated. Therefore, this paper examines the suitability of synthetic vein images generated to compensate for the urgent lack of publicly available large- scale datasets. Firstly, we present an overview of recent research progress of palm vein recognition, from the basic background knowledge to vein anatomical structure, data acquisition, public database, and quality assessment procedures. Then, we focus on the state-of-the-art methods that have allowed the generation of vascular structures for biometric purposes and the modeling of biological networks with their respective application domains. In addition, we review the existing research on the generation of style transfer and biological nature-based synthetic palm vein images algorithms. Afterward, we formalize a general flowchart for the creation of a synthetic database comparing real palm vein images and generated synthetic samples to obtain some understanding into the development of the realistic vein imaging system. Ultimately, we conclude by discussing the challenges, insights, and future perspectives in generating synthetic palm vein images for further works.es_CL
dc.language.isoenes_CL
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/*
dc.sourceInformation Fusion, 89, 66-90es_CL
dc.subjectBiometricses_CL
dc.subjectImage synthesises_CL
dc.subjectPalm vein recognitiones_CL
dc.subjectPalm vein datasetses_CL
dc.subjectSynthetic palm vein imageses_CL
dc.titleTowards the generation of synthetic images of palm vein patterns: a reviewes_CL
dc.typeArticlees_CL
dc.ucm.facultadFacultad de Ciencias Básicases_CL
dc.ucm.indexacionScopuses_CL
dc.ucm.indexacionIsies_CL
dc.ucm.urisciencedirect.com/science/article/pii/S1566253522001026?via%3Dihubes_CL
dc.ucm.doidoi.org/10.1016/j.inffus.2022.08.008es_CL


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Atribución-NoComercial-SinDerivadas 3.0 Chile
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