Fusion of Statistical and Structural Information for Flowchart Recognition

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...

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Bibliographic Details
Main Authors: Carton, Ceres, Lemaitre, Aurelie, Couasnon, Bertrand
Format: Conference Proceeding
Language:English
Subjects:
Context
flowchart recognition
fusion of information
Handwriting recognition
Semantics
Shape
statistical analysis
structural document recognition
structural knowledge
Syntactics
Text recognition
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Description
Summary: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.
ISSN:1520-5363
2379-2140
DOI:10.1109/ICDAR.2013.245