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Title: | Writer identification approach by holistic graphometric features using off-line handwritten words | Authors: | Vásquez, José L. Dutta, Malay Kishore Travieso González, Carlos Manuel Ravelo García, Antonio Gabriel Alonso Hernández, Jesús Bernardino |
UNESCO Clasification: | 3307 Tecnología electrónica | Keywords: | Based-handwriting recognition Word holistic analysis Graphometric features Off-line system Biometric identification | Issue Date: | 2020 | Publisher: | 0941-0643 | Project: | Generacion de Un Marco Unificado Para El Desarrollo de Patrones Biometricos de Comportamiento | Journal: | Neural Computing and Applications | Abstract: | The biometric identification is an important topic with applications in different fields. Among the different modalities, based-handwriting biometric is a very useful and extended modality, and the most known one is the signature. The use of handwritten texts is researched presenting a biometric system for identifying writers from their handwritten words. A set of feature-based graphometric information has been extracted from off-line handwritten words to implement an automatic biometric approach. Given the handwritten nature of the information and its great variability, a feature selection based on principal component analysis and neural network classifier has been proposed. A fusion block based on neural networks has been added in order to reduce the effect of the data variability due to an increase and stabilization of the accuracy. A dataset composed of 100 writers have been used for the experiments. A holdout cross-validation was applied and the accuracy reached between 99.80% and 100% | URI: | http://hdl.handle.net/10553/43949 | ISSN: | 0941-0643 | DOI: | 10.1007/s00521-018-3461-x | Source: | Neural Computing and Applications [ISSN 0941-0643], n. 32(20), p. 15733–15746 |
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