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1 LITIS - Laboratoire d-Informatique, de Traitement de l-Information et des Systèmes 2 L3I - Laboratoire Informatique, Image et Interaction 3 SAGE SAGE - Systèmes Avancés en Génie Électrique

Abstract : To reach the objective of ensuring the indexing and retrieval of digitized resources and offering a structured access to large sets of cultural heritage documents, a raising interest to historical document image segmentation has been generated. In fact, there is a real need for automatic algorithms ensuring the identification of homogeneous regions or similar groups of pixels sharing some visual characteristics from historical documents i.e. distinguishing graphic types, segmenting graphical regions from textual ones, and discriminating text in a variety of situations of different fonts and scales. Indeed, determining graphic regions can help to segment and analyze the graphical part in historical heritage, while finding text zones can be used as a pre-processing stage for character recognition, text line extraction, handwriting recognition, etc. Thus, we propose in this article an automatic segmentation method for historical document images based on extraction of homogeneous or similar content regions. The proposed algorithm is based on using simple linear iterative clustering SLIC su-perpixels, Gabor filters, multi-scale analysis, majority voting technique, connected component analysis, color layer separation, and an adaptive run-length smoothing algorithm ARLSA. It has been evaluated on 1000 pages of historical documents and achieved interesting results.

Keywords : Multi-scale analysis ARLSA Historical document images Segmentation SLIC superpixels Gabor filters

Author: Maroua Mehri - Pierre Héroux - Nabil Sliti - Petra Gomez-Krämer - Najoua Essoukri Ben Amara - Rémy Mullot -

Source: https://hal.archives-ouvertes.fr/


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