Abstract
In the paper we present an approach to the automatic segmentation of interesting elements from paper documents i.e. stamps, logos, printed text blocks, signatures, and tables. Presented approach involves object detection by means of Convolutional Neural Network. Resulting regions are then subjected to integration based on confidence level and shape. Experiments performed on representative set of digitizsed paper documents proved usefulness and efficiency of the developed approach. The results were compared with the standard cascade-based detection and showed the superiority of the CNN-based approach.
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Forczmański, P., Smoliński, A., Nowosielski, A., Małecki, K. (2020). Segmentation of Scanned Documents Using Deep-Learning Approach. In: Burduk, R., Kurzynski, M., Wozniak, M. (eds) Progress in Computer Recognition Systems. CORES 2019. Advances in Intelligent Systems and Computing, vol 977. Springer, Cham. https://doi.org/10.1007/978-3-030-19738-4_15
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DOI: https://doi.org/10.1007/978-3-030-19738-4_15
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