research-article

Table Detection in Online Ink Notes

Authors:

Zhicheng Zhong,

Heung-Yeung ShumAuthors Info & Claims

IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 28, Issue 8

Pages 1341 - 1346

https://doi.org/10.1109/TPAMI.2006.173

Published: 01 August 2006 Publication History

Abstract

In documents, tables are important structured objects that present statistical and relational information. In this paper, we present a robust system which is capable of detecting tables from free style online ink notes and extracting their structure so that they can be further edited in multiple ways. First, the primitive structure of tables, i.e., candidates for ruling lines and table bounding boxes, are detected among drawing strokes. Second, the logical structure of tables is determined by normalizing the table skeletons, identifying the skeleton structure, and extracting the cell contents. The detection process is similar to a decision tree so that invalid candidates can be ruled out quickly. Experimental results suggest that our system is robust and accurate in dealing with tables having complex structure or drawn under complex situations.

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Cited By

Julca-Aguilar FMouchère HViard-Gaudin CHirata N(2020)A general framework for the recognition of online handwritten graphicsInternational Journal on Document Analysis and Recognition10.1007/s10032-019-00349-623:2(143-160)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1007/s10032-019-00349-6
Delaye ALiu C(2014)Contextual text/non-text stroke classification in online handwritten notes with conditional random fieldsPattern Recognition10.1016/j.patcog.2013.04.01747:3(959-968)Online publication date: 1-Mar-2014
https://dl.acm.org/doi/10.1016/j.patcog.2013.04.017
Delaye ALiu C(2014)Multi-class segmentation of free-form online documents with tree conditional random fieldsInternational Journal on Document Analysis and Recognition10.1007/s10032-014-0221-z17:4(313-329)Online publication date: 1-Dec-2014
https://dl.acm.org/doi/10.1007/s10032-014-0221-z

Index Terms

Table Detection in Online Ink Notes
1. Applied computing
  1. Document management and text processing
    1. Document capture
      1. Document analysis
2. Computing methodologies
  1. Machine learning
    1. Machine learning algorithms
      1. Feature selection

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Information

Published In

cover image IEEE Transactions on Pattern Analysis and Machine Intelligence

IEEE Transactions on Pattern Analysis and Machine Intelligence Volume 28, Issue 8

August 2006

172 pages

ISSN:0162-8828

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Copyright © 2006.

Publisher

IEEE Computer Society

United States

Publication History

Published: 01 August 2006

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Cited By

Julca-Aguilar FMouchère HViard-Gaudin CHirata N(2020)A general framework for the recognition of online handwritten graphicsInternational Journal on Document Analysis and Recognition10.1007/s10032-019-00349-623:2(143-160)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1007/s10032-019-00349-6
Delaye ALiu C(2014)Contextual text/non-text stroke classification in online handwritten notes with conditional random fieldsPattern Recognition10.1016/j.patcog.2013.04.01747:3(959-968)Online publication date: 1-Mar-2014
https://dl.acm.org/doi/10.1016/j.patcog.2013.04.017
Delaye ALiu C(2014)Multi-class segmentation of free-form online documents with tree conditional random fieldsInternational Journal on Document Analysis and Recognition10.1007/s10032-014-0221-z17:4(313-329)Online publication date: 1-Dec-2014
https://dl.acm.org/doi/10.1007/s10032-014-0221-z

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