Structural Mixtures for Statistical Layout Analysis

Beusekom, Joost van; Keysers, Daniel; Breuel, Thomas M.

doi:10.1109/das.2008.61

Cited by 10 publications

(3 citation statements)

References 20 publications

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“…This method has been successfully applied to many layouts [41], such as correspondence letters, administrative documents, historical newspapers or musical scores. Although, some analysis is based on bottom-up analysis A probabilistic method was introduced by Shafait et al [62]. For each document, the method returns the most probable zones, using a prior user-defined breakdown.…”

Section: Top-down Strategiesmentioning

confidence: 99%

Combination of deep neural networks and logical rules for record segmentation in historical handwritten registers using few examples

Tarride

Lemaitre

Coüasnon

et al. 2021

IJDAR

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This work focuses on the layout analysis of historical handwritten registers, in which local religious ceremonies were recorded. The aim of this work is to delimit each record in these registers. To this end, two approaches are proposed. Firstly, object detection networks are explored, as three state-of-the-art architectures are compared. Further experiments are then conducted on Mask R-CNN, as it yields the best performance. Secondly, we introduce and investigate Deep Syntax, a hybrid system that takes advantages of recurrent patterns to delimit each record, by combining ushaped networks and logical rules. Finally, these two approaches are evaluated on 3708 French records (16-18th centuries), as well as on the Esposalles public database, containing 253 Spanish records (17th century). While both systems perform well on homogeneous documents, we observe a significant drop in performance with Mask R-CNN on heterogeneous documents, especially when trained on a non-representative subset. By contrast, Deep Syntax relies on steady patterns, and is therefore able to process a wider range of documents with less training data. Not only Deep Syntax produces 15% more match configurations and reduces the ZoneMap surface error metric by 30% when both systems are trained on 120 images, but it also outperforms Mask R-CNN when trained on a database three times smaller. As Deep Syntax generalizes better, we believe it can be used in the context of massive document processing, as collecting and annotating a sufficiently large and representative set of training data is not always achievable.

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Section: Top-down Strategiesmentioning

confidence: 99%

Combination of deep neural networks and logical rules for record segmentation in historical handwritten registers using few examples

Tarride

Lemaitre

Coüasnon

et al. 2021

IJDAR

View full text Add to dashboard Cite

show abstract

“…The algorithms that make clear assumptions about the document layout [15,26,[33][34][35][36][37][38][39][40][41]: they either define this layout with a grammar, a set of rules or they assume that it is a Manhattan layout and use projection profiles.…”

Section: The Algorithms In Group Onementioning

confidence: 99%

“…There are five algorithms of this type [26,[33][34][35][36]. They were first published in 2006 by Coüasnon [117] and tested on a data set of 88745 documents which is an unrivaled data set size.…”

Section: Grammarmentioning

confidence: 99%

A comprehensive survey of mostly textual document segmentation algorithms since 2008

Eskenazi

Gomez‐Krämer

Ogier

2017

Pattern Recognition

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International audienceIn 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

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Printed and scanned document authentication using robust layout descriptor matching

Gomez-Krämer,

Rouis,

Diallo

et al. 2023

Multimed Tools Appl

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Structural Mixtures for Statistical Layout Analysis

Cited by 10 publications

References 20 publications

Combination of deep neural networks and logical rules for record segmentation in historical handwritten registers using few examples

Combination of deep neural networks and logical rules for record segmentation in historical handwritten registers using few examples

A comprehensive survey of mostly textual document segmentation algorithms since 2008

Printed and scanned document authentication using robust layout descriptor matching

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