Text Independent Writer Identification from Online Handwriting

Abstract : Automatic identification of the author of a document has a variety of applications for both online and offline handwritten data such as facilitating the use of writerdependent recognizers, verification of claimed identity for security, enabling personalized HCI and countering repudiations for legal purposes. Most of the existing writer identification techniques require the data to be from a specific text or a recognizer be available, which is not always feasible. Text-independent approaches often require large amount of data to be confident of good results. In this work, we propose a text-independent writer identification framework that uses a specified set of primitives of online handwritten data to ascertain the identity of the writer. The framework allows us to learn the properties of the script and the writers simultaneously and hence can be used with multiple languages or scripts. We demonstrate the applicability of our framework by choosing shapes of curves as primitives and show results on five different scripts and on different data sets.
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Communication dans un congrès
Guy Lorette. Tenth International Workshop on Frontiers in Handwriting Recognition, Oct 2006, La Baule (France), Suvisoft, 2006
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Soumis le : lundi 9 octobre 2006 - 15:36:22
Dernière modification le : lundi 9 octobre 2006 - 15:51:27
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  • HAL Id : inria-00104859, version 1

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Anoop Namboodiri, Sachin Gupta. Text Independent Writer Identification from Online Handwriting. Guy Lorette. Tenth International Workshop on Frontiers in Handwriting Recognition, Oct 2006, La Baule (France), Suvisoft, 2006. 〈inria-00104859〉

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