IAMonDo-database: an online handwritten document database with non-uniform contents. In this paper we present a new database of online handwritten documents with different contents such as text, drawings, diagrams, formulas, tables, lists, and markings. It was designed to serve as a standard dataset for the development, training, testing and comparison of methods in the field of handwritten document analysis. The database can serve as a basis for layout analysis, and different segmentation and recognition tasks considering online or just offline information. Its size is 1,000 documents produced by approximately 200 writers including a total of 329,849 online strokes. Few constraints were imposed on the writers when creating the documents. Nonetheless, the database has a stable distribution of the different content types. A software tool was developed to allow easy access to the documents which are stored in InkML. In this paper we also present two experiments which show the challenge this database poses. They may figure as references for further research in this area.

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References in zbMATH (referenced in 2 articles )

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  1. Delaye, Adrien; Liu, Cheng-Lin: Contextual text/non-text stroke classification in online handwritten notes with conditional random fields (2014) ioport
  2. Doermann, David (ed.); Tombre, Karl (ed.): Handbook of document image processing and recognition (2014)