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Title: Multi-oriented text recognition in graphical documents using HMM
Authors: Pratim Roy, Partha
Roy S.
Pal U.
Published in: Proceedings of 11th IAPR International Workshop on Document Analysis Systems, DAS 2014
Abstract: The text lines in graphical documents (e.g., maps, engineering drawings), artistic documents etc., are often annotated in curve lines to illustrate different locations or symbols. For the optical character recognition of such documents, individual text lines from the documents need to be extracted and recognized. Due to presence of multi-oriented characters in such non-structured layout, word recognition is a challenging task. In this paper, we present an approach towards the recognition of scale and orientation invariant text words in graphical documents using Hidden Markov Models (HMM). First, a line extraction method is applied to segment text lines and the method is based on the foreground and background information of the text components. To effectively utilize the background information, a water reservoir concept is used here. For recognition of curved text lines, a path of sliding window is estimated and features extracted from the sliding window are fed to the HMM system for recognition. Local gradient histogram (LGH) based frame-wise feature is used in HMM. The experimental results are evaluated on a dataset of graphical words and we have obtained encouraging results. © 2014 IEEE.
Citation: Proceedings of 11th IAPR International Workshop on Document Analysis Systems, DAS 2014, (2014), 136- 140. Tours
Issue Date: 2014
Publisher: IEEE Computer Society
Keywords: Formatting
ISBN: 9.78148E+12
Author Scopus IDs: 56880478500
Author Affiliations: Roy, P.P., CVPR Unit, Indian Statistical Institute, Kolkata, India
Roy, S., Tata Consultancy Services, Kolkata, India
Pal, U., CVPR Unit, Indian Statistical Institute, Kolkata, India
Appears in Collections:Conference Publications [CS]

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