Fusion of statistical and structural information for flowchart recognition - Archive ouverte HAL Access content directly
Conference Papers Year : 2013

Fusion of statistical and structural information for flowchart recognition

(1) , (1) , (1)
1

Abstract

A critical step of on-line handwritten diagram recognition is the segmentation between text and symbols. It is still an open problem in several approaches of the literature. However, for a human operator, text/symbol segmentation is an easy task and does not even need understanding diagram semantics. It is done thanks to the use of both structural knowledge and statistical analysis. A human operator knows what is a symbol and how to distinguish a good symbol from a bad one in a list of candidates. We propose to reproduce this perceptive mechanism by introducing some statistical information inside of a grammatical method for document structure recognition, in order to combine both structural an statistical knowledge. This approach is applied to flowchart recognition on a freely available database. The results demonstrate the interest of combining statistical and structural information for perceptive vision in diagram recognition.
Fichier principal
Vignette du fichier
article_icdar.pdf (211.85 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00921640 , version 1 (24-03-2014)

Identifiers

  • HAL Id : hal-00921640 , version 1

Cite

Cérès Carton, Aurélie Lemaitre, Bertrand Couasnon. Fusion of statistical and structural information for flowchart recognition. ICDAR - International Conference on Document Analysis and Recognition, 2013, Washington, United States. pp.1242-1246. ⟨hal-00921640⟩
254 View
340 Download

Share

Gmail Facebook Twitter LinkedIn More