Handwritten Document Analysis for Automatic Writer Recognition
In this paper, we show that both the writer identification and the writer verification tasks can be carried out using local features such as graphemes extracted from the segmentation of cursive handwriting. We thus enlarge the scope of the possible use of these two tasks which have been, up to now,...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2005 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:24339 |
| Acceso en línea: | https://ddd.uab.cat/record/24339 https://dx.doi.org/urn:doi:10.5565/rev/elcvia.97 |
| Access Level: | acceso abierto |
| Palabra clave: | Handwritten documents Writer identification Writer verification Information retrieval Mutual information Hypothesis testing Graphemes Documents manuscrits Identificació d'autor/escriptor Verificació d'autor/escriptor Recuperació de la informació Informació comuna Prova d'hipòtesis Grafemes Documentos manuscritos Identificación de autor / escritor Verificación de autor / escritor Recuperación de la información Información común Prueba de hipótesis Grafemas |
| Sumario: | In this paper, we show that both the writer identification and the writer verification tasks can be carried out using local features such as graphemes extracted from the segmentation of cursive handwriting. We thus enlarge the scope of the possible use of these two tasks which have been, up to now, mainly evaluated on script handwritings. A textual based Information Retrieval model is used for the writer identification stage. This allows the use of a particular feature space based on feature frequencies. Image queries are handwritten documents projected in this feature space. The approach achieves 95% correct identification on the PSI_DataBase and 86% on the IAM_DataBase. Then writer hypothesis retrieved are analysed during a verification phase. We call upon a mutual information criterion to verify that two documents may have been produced by the same writer or not. Hypothesis testing is used for this purpose. The proposed method is first scaled on the PSI_DataBase then evaluated on the IAM_DataBase. On both databases, similar performance of nearly 96% correct verification is reported, thus making the approach general and very promising for large scale applications in the domain of handwritten document querying and writer verification. |
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