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dc.contributor.authorAubin, Verónica
dc.contributor.authorMora, Marco
dc.contributor.authorSantos-Peñas, Matilde
dc.date.accessioned2018-06-06T13:59:39Z
dc.date.available2018-06-06T13:59:39Z
dc.date.issued2018
dc.identifier.urihttp://repositorio.ucm.cl/handle/ucm/1797
dc.description.abstractA method to writer verification based on handwritten stroke analysis is presented. The proposed descriptors correspond to an estimation of the pressure applied when writing using the grayscale image of the stroke. These descriptors are obtained from individual and simple graphemes, in contrast with the complexity of the handwritten stroke used in the signature processing systems. In addition, a study is presented which suggests that the combination of descriptors of simple characters improves the recognition capacity of the method. The descriptors considered correspond to different accuracy degrees of pressure distribution representation. Specifically, from the simplest representation to a more complex one, the descriptors proposed are as follows: the width of the stroke, the gray level of the grapheme skeleton, the average of the gray levels on the perpendicular line to the skeleton, and the approximation transformation coefficients of the area of the grapheme. The advantage of these descriptors is that they are invariant to scale and rotation. The descriptors performance was assessed using the original images and also reduced versions based on traditional methods such as Principal Component Analysis and Discrete Cosine Transform. For the evaluation, a one-vs-all scheme was considered which is consistent with the problem of identity verification. It was implemented with Support Vector Machine classifiers trained with K-Fold Cross Validation. The efficient search of SVM hyperparameters was performed with the heuristic optimization algorithm Simulated Annealing. The evaluation of individual simple characters gives a high average of hits and the combination of characters even improves the performance, getting closer to 100% of hits in identity verification. Qualitative and quantitative comparison with other methods and descriptors has been also carried out with satisfactory results.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.sourcePattern Recognition, 79, 414-426es_CL
dc.subjectWriter verificationes_CL
dc.subjectPseudo-dynamic featureses_CL
dc.subjectSimple graphemeses_CL
dc.subjectOff-line stroke analysises_CL
dc.titleOff-line writer verification based on simple graphemeses_CL
dc.typeArticlees_CL
dc.ucm.facultadFacultad de Ciencias de la Ingenieríaes_CL
dc.ucm.indexacionScopuses_CL
dc.ucm.indexacionIsies_CL
dc.ucm.urisibib2.ucm.cl:2048/login?url=https://www.sciencedirect.com/science/article/pii/S0031320318300773es_CL
dc.ucm.doidoi.org/10.1016/j.patcog.2018.02.024es_CL


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Atribución-NoComercial-SinDerivadas 3.0 Chile
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