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New algorithm for skewing detection of handwritten Bangla words


Ghosh, R and Bhattacharyya, D and Kim, TH and Lee, G-S, New algorithm for skewing detection of handwritten Bangla words, Communications in Computer and Information Science 260: Proceedings of the 2011 International Conference on Signal Processing, Image Processing and Pattern Recognition, 8-10 December 2011, Jeju Island, South Korea, pp. 153-159. ISBN 978-3-642-27182-3 (2011) [Refereed Conference Paper]

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Copyright 2011 Springer-Verlag Berlin Heidelberg

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DOI: doi:10.1007/978-3-642-27183-0_16


Segmentation of a word into basic characters or strokes is an essential and necessary preprocessing step for character recognition in many handwritten word recognition systems, especially in case of handwritten bangla words. The major difficulty in character segmentation is the cursive script. This is because different person have different styles for their handwriting. Here, in this article a novel approach for skew detection followed by skew correction has been presented for online handwritten Bangla words. Here, we have used a slight variation of the projection profile method to calculate the amount of skew in an online Bangla handwritten word. The algorithm has been verified on a database of words collected from different people.

Item Details

Item Type:Refereed Conference Paper
Keywords:image processing, segmentation, recognition, database
Research Division:Information and Computing Sciences
Research Group:Computer vision and multimedia computation
Research Field:Image processing
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the information and computing sciences
UTAS Author:Kim, TH (Dr Tai Kim)
ID Code:120718
Year Published:2011
Deposited By:Information and Communication Technology
Deposited On:2017-08-30
Last Modified:2018-02-02

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