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Conference papers

Families of Markov models for document image segmentation

Christian Wolf 1 
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : In this paper we compare several directed and undirected graphical models for different image segmentation problems in the domain of document image processing and analysis. We show that adapting the structure of the model to specific sitations at hand, for instance character restoration, recto/verso separation and segmenting high resolution character images, can significantly improve segmentation performance. We propose inference algorithms for the different models and we test them on different data sets.
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Submitted on : Tuesday, January 17, 2017 - 1:57:15 PM
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Christian Wolf. Families of Markov models for document image segmentation. Machine Learning for Signal Processing Workshop, Sep 2009, Grenoble, France. pp.6, ⟨10.1109/MLSP.2009.5306241⟩. ⟨hal-01437733⟩



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