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Extraction of Homogeneous Regions in Historical Document Images

文献类型： 会议论文

第一作者： Maroua Mehri

作者： Maroua Mehri 1 ; Pierre Heroux 2 ; Nabil Sliti 3 ; Petra Gomez-Kramer 1 ; Najoua Essoukri Ben Amara 3 ; Remy Mullot 2 ;

作者机构： 1.L3i, University of La Rochelle

2.LITIS, University of Rouen, Avenue de l'Universite

3.SAGE, University of Sousse, Ecole Nationale d'Ingenieurs de Sousse

关键词： Historical Document Images;Segmentation;SLIC Superpixels;Gabor Filters;Multi-Scale Analysis;ARLSA

会议名称： International Conference on Computer Vision Theory and Applications

主办单位：

页码： 40-47

摘要： 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resources and offering a structured access to large sets of cultural heritage documents, a raising interest to historical document image segmentation has been generated.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ensuring the identification of homogenous regions or similar groups of pixels sharing some visual characteristics from historical documents (i.e. distinguishing graphic types, segmenting graphical regions from textual ones, and discriminating text in a variety of situations of different fonts and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 Thus, we propose in this article an automatic segmentation method for historical document images based on extraction of homogeneous or similar content regions.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) superpixels, 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 It has been evaluated on 1000 pages of historical documents and achieved interesting results.

分类号： TP391.41-53

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