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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 7423)
Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Conference series link(s): GREC: International Workshop on Graphics Recognition
Conference proceedings info: GREC 2011.
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Table of contents (25 papers)
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Front Matter
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Session 2: Symbol and Logo Recognition
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Session 3: Sketch and Drawings
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Session 4: Performance Evaluation
About this book
This book constitutes the thoroughly refereed post-conference proceedings of the 9th International Workshop on Graphics Recognition (GREC 2011), held in Seoul, Korea, September 15-16, 2011. The 25 revised full papers presented were carefully selected from numerous submissions. Graphics recognition is a subfield of document image analysis that deals with graphical entities in engineering drawings, sketches, maps, architectural plans, musical scores, mathematical notation, tables, and diagrams. Accordingly the conference papers are organized in 5 technical sessions, covering the topics such as map and ancient documents, symbol and logo recognition, sketch and drawings, performance evaluation and challenge processing.
Editors and Affiliations
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Department of Computer Science and Engineering, Chung-Ang University, Dongjakku, Korea
Young-Bin Kwon
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Laboratoire L3i, Université de La Rochelle, La Rochelle Cedex 1, France
Jean-Marc Ogier
Bibliographic Information
Book Title: Graphics Recognition
Book Subtitle: New Trends and Challenges
Editors: Young-Bin Kwon, Jean-Marc Ogier
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-642-36824-0
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2013
Softcover ISBN: 978-3-642-36823-3Published: 10 February 2013
eBook ISBN: 978-3-642-36824-0Published: 11 February 2013
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XII, 275
Number of Illustrations: 162 b/w illustrations
Topics: Natural Language Processing (NLP), Image Processing and Computer Vision