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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15961
Title: Touching text character localization in graphical documents using SIFT
Authors: Pratim Roy, Partha
Pal U.
Lladós J.
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract: Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult. Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches. © 2010 Springer-Verlag.
Citation: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), (2010), 199- 211. La Rochelle
URI: https://doi.org/10.1007/978-3-642-13728-0_18
http://repository.iitr.ac.in/handle/123456789/15961
Issue Date: 2010
Keywords: Document images
Document recognition
Object descriptors
Pattern recognition and classification
Scale invariant feature transforms
SIFT Feature
State-of-the-art approach
Symbol recognition
Object recognition
Wavelet transforms
Character recognition
ISBN: 364213727X; 9783642137273
ISSN: 3029743
Author Scopus IDs: 56880478500
57200742116
6603062543
Author Affiliations: Roy, P.P., Computer Vision Center, Universitat Autònoma de Barcelona, Bellaterra (Barcelona) 08193, Spain
Pal, U., Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata 108, India
Lladós, J., Computer Vision Center, Universitat Autònoma de Barcelona, Bellaterra (Barcelona) 08193, Spain
Corresponding Author: Roy, P. P.; Computer Vision Center, Universitat Autònoma de Barcelona, Bellaterra (Barcelona) 08193, Spain
Appears in Collections:Conference Publications [CS]

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