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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15733
Title: Convex hull based approach for multi-oriented character recognition from graphical documents
Authors: Pratim Roy, Partha
Pal U.
Lladós J.
Kimura F.
Published in: Proceedings of International Conference on Pattern Recognition
Abstract: In this paper, we present a scheme towards recognition of English character in multi-scale and multi-oriented environments. Graphical document such as map consists of text lines which appear in different orientation. Sometimes, characters in a single word may follow a curvi-linear way to annotate the graphical curve lines. For recognition of such multi-scale and multi-oriented characters a Support Vector Machine (SVM) based scheme is presented in this paper. The feature used here is invariant to character orientation. Circular ring and convex hull have been used along with angular information of the contour pixels of the character to make the feature rotation invariant. We tested our proposed scheme on two different datasets. Combining circular and convex hull feature we have obtained 96.73% and 99.56% accuracy in these two datasets. © 2008 IEEE.
Citation: Proceedings of International Conference on Pattern Recognition, (2008). Tampa, FL
URI: http://repository.iitr.ac.in/handle/123456789/15733
Issue Date: 2008
Keywords: Character orientation
Circular ring
Convex hull
Data sets
Multiscales
Rotation invariant
Text lines
Character recognition
Computational geometry
ISBN: 9.78142E+12
ISSN: 10514651
Author Scopus IDs: 56880478500
57200742116
6603062543
55247906100
Author Affiliations: Roy, P.P., Computer Vision Center, Universitat Autònoma De Barcelona, 08193, Bellaterra, Spain
Pal, U., Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata - 108, India
Lladós, J., Computer Vision Center, Universitat Autònoma De Barcelona, 08193, Bellaterra, Spain
Kimura, F., Graduate School of Engineering, Mie University, 1577 Kurimamachiya, Mie 514-8504, Japan
Corresponding Author: Roy, P. P.; Computer Vision Center, Universitat Autònoma De Barcelona, 08193, Bellaterra, Spain; email: partha@cvc.uab.es
Appears in Collections:Conference Publications [CS]

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