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  1. International Journal of Document Analysis and Recognition (IJDAR)
  2. International Journal of Document Analysis and Recognition (IJDAR) : Volume 14
  3. International Journal of Document Analysis and Recognition (IJDAR) : Volume 14, Issue 1, March 2011
  4. A protocol to characterize the descriptive power and the complementarity of shape descriptors
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International Journal of Document Analysis and Recognition (IJDAR) : Volume 20
International Journal of Document Analysis and Recognition (IJDAR) : Volume 19
International Journal of Document Analysis and Recognition (IJDAR) : Volume 18
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17
International Journal of Document Analysis and Recognition (IJDAR) : Volume 16
International Journal of Document Analysis and Recognition (IJDAR) : Volume 15
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14, Issue 4, December 2011
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14, Issue 3, September 2011
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14, Issue 2, June 2011
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14, Issue 1, March 2011
Editorial
ICDAR 2009-Arabic handwriting recognition competition
On-line Arabic handwriting recognition competition : ADAB database and participating systems
ICDAR2009 handwriting segmentation contest
DIBCO 2009: document image binarization contest
Setting up a competition framework for the evaluation of structure extraction from OCR-ed books
SCUT-COUCH2009—a comprehensive online unconstrained Chinese handwriting database and benchmark evaluation
Grammar-based techniques for creating ground-truthed sketch corpora
EMERS: a tree matching–based performance evaluation of mathematical expression recognition systems
A protocol to characterize the descriptive power and the complementarity of shape descriptors
Metrics for evaluating performance in document analysis: application to tables
International Journal of Document Analysis and Recognition (IJDAR) : Volume 13
International Journal of Document Analysis and Recognition (IJDAR) : Volume 12
International Journal of Document Analysis and Recognition (IJDAR) : Volume 11
International Journal of Document Analysis and Recognition (IJDAR) : Volume 10
International Journal of Document Analysis and Recognition (IJDAR) : Volume 9
International Journal of Document Analysis and Recognition (IJDAR) : Volume 8
International Journal of Document Analysis and Recognition (IJDAR) : Volume 7
International Journal of Document Analysis and Recognition (IJDAR) : Volume 6
International Journal of Document Analysis and Recognition (IJDAR) : Volume 5
International Journal of Document Analysis and Recognition (IJDAR) : Volume 4
International Journal of Document Analysis and Recognition (IJDAR) : Volume 3
International Journal of Document Analysis and Recognition (IJDAR) : Volume 2
International Journal of Document Analysis and Recognition (IJDAR) : Volume 1

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A protocol to characterize the descriptive power and the complementarity of shape descriptors

Content Provider SpringerLink
Author Visani, Muriel Terrades, Oriol Ramos Tabbone, Salvatore
Copyright Year 2010
Abstract Most document analysis applications rely on the extraction of shape descriptors, which may be grouped into different categories, each category having its own advantages and drawbacks (O.R. Terrades et al. in Proceedings of ICDAR’07, pp. 227–231, 2007). In order to improve the richness of their description, many authors choose to combine multiple descriptors. Yet, most of the authors who propose a new descriptor content themselves with comparing its performance to the performance of a set of single state-of-the-art descriptors in a specific applicative context (e.g. symbol recognition, symbol spotting...). This results in a proliferation of the shape descriptors proposed in the literature. In this article, we propose an innovative protocol, the originality of which is to be as independent of the final application as possible and which relies on new quantitative and qualitative measures. We introduce two types of measures: while the measures of the first type are intended to characterize the descriptive power (in terms of uniqueness, distinctiveness and robustness towards noise) of a descriptor, the second type of measures characterizes the complementarity between multiple descriptors. Characterizing upstream the complementarity of shape descriptors is an alternative to the usual approach where the descriptors to be combined are selected by trial and error, considering the performance characteristics of the overall system. To illustrate the contribution of this protocol, we performed experimental studies using a set of descriptors and a set of symbols which are widely used by the community namely ART and SC descriptors and the GREC 2003 database.
Starting Page 87
Ending Page 100
Page Count 14
File Format PDF
ISSN 14332833
Journal International Journal of Document Analysis and Recognition (IJDAR)
Volume Number 14
Issue Number 1
e-ISSN 14332825
Language English
Publisher Springer-Verlag
Publisher Date 2010-09-23
Publisher Place Berlin, Heidelberg
Access Restriction Subscribed
Subject Keyword Document analysis Shape descriptors Symbol description Performance characterization Complementarity analysis Pattern Recognition Image Processing and Computer Vision
Content Type Text
Resource Type Article
Subject Computer Vision and Pattern Recognition Software Computer Science Applications
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