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Generating style-based palm vein synthetic images for the creation of large-scale datasets
| dc.contributor.author | Salazar, E. | |
| dc.contributor.author | Hernández-García, Ruber | |
| dc.contributor.author | Barrientos, Ricardo | |
| dc.contributor.author | Vilches-Ponce, Karina | |
| dc.contributor.author | Mora, Marco | |
| dc.contributor.author | Vásquez, A. | |
| dc.date.accessioned | 2022-08-24T16:32:29Z | |
| dc.date.available | 2022-08-24T16:32:29Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | http://repositorio.ucm.cl/handle/ucm/4016 | |
| dc.description.abstract | Individuals recognition through their biometric traits is an essential component of modern society. The recent literature includes several works based on palm vein recognition for individual identification, being a very active research field in the last five years. However, the publicly available datasets are very limited and have a small number of subjects, which limits to conduct scalability tests on large-scale databases. In this work, we propose a novel specific domain application for stylebased GAN architecture (StyleGAN) for generating synthetic palm vein images. Moreover, we present the largest dataset of palm vein images of the state-of-the-art at this moment, comprising of 10,000 subjects with 6 samples per each. Experimental results show that generated images look very realistic based on different metrics for measuring them against prior real datasets. The proposed dataset, called Synthetic Style-based Palm Vein Database (Synthetic-sPVDB), is publicly available on the website of our laboratory. | es_CL |
| dc.language.iso | en | es_CL |
| dc.rights | Atribución-NoComercial-SinDerivadas 3.0 Chile | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/cl/ | * |
| dc.source | IET Conference Publications, 2021(CP773), 182-187 | es_CL |
| dc.subject | Biometrics | es_CL |
| dc.subject | Neural nets | es_CL |
| dc.subject | Vein recognition | es_CL |
| dc.title | Generating style-based palm vein synthetic images for the creation of large-scale datasets | es_CL |
| dc.type | Article | es_CL |
| dc.ucm.indexacion | Scopus | es_CL |
| dc.ucm.uri | ieeexplore.ieee.org/document/9568990 | es_CL |
| dc.ucm.doi | doi.org/10.1049/icp.2021.1451 | es_CL |
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