A comprehensive survey of mostly textual document segmentation algorithms since 2008

被引：68
作者：
Eskenazi, Sebastien [1 ]
Gomez-Kramer, Petra [1 ]
Ogier, Jean-Marc [1 ]
机构：
[1] La Rochelle Univ, Lab L3i, Ave Michel Crepeau, F-17042 La Rochelle, France
来源：
PATTERN RECOGNITION | 2017年 / 64卷
关键词：
Document; Segmentation; Survey; Evaluation; Trends; Typology; OF-THE-ART; LAYOUT ANALYSIS; LINE SEGMENTATION; PAGE SEGMENTATION; IMAGE-ANALYSIS; HANDWRITTEN; EXTRACTION; MODEL; CRF;
D O I：
10.1016/j.patcog.2016.10.023
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：1 / 14
页数：14
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