A comprehensive survey of mostly textual document segmentation algorithms since 2008. (April 2017)

• Record Type: Journal Article
• Authors: Eskenazi, Sébastien; Gomez-Krämer, Petra; Ogier, Jean-Marc
• Is Part Of: Pattern recognition. Volume 64(2017:Apr.)
• Page Start: 1
• Page End: 14
• Publication Date: 2017-04
• Subjects: Document -- Segmentation -- Survey -- Evaluation -- Trends -- Typology; Pattern perception -- Periodicals; Perception des structures -- Périodiques; Patroonherkenning; 006.4
• DOI: 10.1016/j.patcog.2016.10.023
• Languages: English
• ISSNs: 0031-3203

Abstract

Abstract: In document image analysis, segmentation is the task that identifies the regions of a document. The increasing number of applications of document analysis requires a good knowledge of the available technologies. This survey highlights the variety of the approaches that have been proposed for document image segmentation since 2008. It provides a clear typology of documents and of document image segmentation algorithms. We also discuss the technical limitations of these algorithms, the way they are evaluated and the general trends of the community. Abstract : Highlights: Extensive review of the state of the art with a well defined scope. Analysis of the algorithms from a scientific and an industrial point of view. Well defined document and algorithm typologies. Discussion on the trends of the field and the evaluation of the algorithms.