Kalman Filter Contributions Towards Document Segmentation

Charles Queguiner 1 Jean Camillerapp 1 Ivan Leplumey 1
1 IMADOC - Interprétation et Reconnaissance d’Images et de Documents
UR1 - Université de Rennes 1, INSA Rennes - Institut National des Sciences Appliquées - Rennes, CNRS - Centre National de la Recherche Scientifique : UMR6074
Abstract : One way of tackling document analysis is to split the document into different layers and then find a segmentation for each one. The straight line is often one of the basic elements of the layers making a document. The dectection of these segments is often disturbed by the superposition of different layers in the same area. Therefore we developed a segment extractor, which processes masked areas, discontinuities ans even curvatures. After showing in our previous work, the interest of such a system in binary image analysis, our aim was to show the method could be generalized to grey level images, by taking into account pixel luminosity as one of the parameters. The Kalman filter method combined with an adequate control scheme, allows the pooling of local observations, when their position, width and luminosity are coherent. The proposed model gives an interesting scheme to manage drawings masking each other (eg. cross-lines).
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Conference papers
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https://hal.inria.fr/hal-00763395
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Submitted on : Monday, December 10, 2012 - 4:43:44 PM
Last modification on : Friday, November 16, 2018 - 1:28:16 AM
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Charles Queguiner, Jean Camillerapp, Ivan Leplumey. Kalman Filter Contributions Towards Document Segmentation. ICDAR 1995 Third International Conference on Document Analysis and Recognition, Aug 1995, Montreal, Canada. pp.765-769. ⟨hal-00763395⟩

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