Abstract
The process of obtaining the logical structure of a given document from its geometric structure is known as document understanding. In this process, it is important to classify the distinct blocks or homogeneous regions that the document contains as reliably as possible. In this work, we propose a neural-based method to classify among manuscript text, typed text, drawings and photographic images. The excellent performance of the approach is demonstrated by the experiments performed.
Work partially supported by the Spanish CICYT under contract TIC2000-1153.
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López, D., Castro, M.J. (2002). Neural-Based Classification of Blocks from Documents. In: Dorronsoro, J.R. (eds) Artificial Neural Networks — ICANN 2002. ICANN 2002. Lecture Notes in Computer Science, vol 2415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46084-5_88
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DOI: https://doi.org/10.1007/3-540-46084-5_88
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