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Segmentation of Handwritten Documents Containing Kannada Script

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Saleem Pasha, M. C. Padma
10.5120/ijca2016910485

Saleem Pasha and M C Padma. Segmentation of Handwritten Documents Containing Kannada Script. International Journal of Computer Applications 144(12):1-6, June 2016. BibTeX

@article{10.5120/ijca2016910485,
	author = {Saleem Pasha and M. C. Padma},
	title = {Segmentation of Handwritten Documents Containing Kannada Script},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2016},
	volume = {144},
	number = {12},
	month = {Jun},
	year = {2016},
	issn = {0975-8887},
	pages = {1-6},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume144/number12/25228-2016910485},
	doi = {10.5120/ijca2016910485},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Segmentation is one of the important phases of Optical Character Recognition (OCR) system, which extracts objects of interest from an image. Feature extraction and classification phases of OCR will be more effective, if the techniques selected for segmentation is effective. This paper focuses on to develop a system for handwritten documents containing Kannada script and proposes suitable techniques to perform preprocessing and also segmentation such as line, word and character segmentation. Novelty is achieved by proposing a modified horizontal projection profile method for line segmentation, in which well separated lines and overlapping lines are detected. An average accuracy of 97.5% is achieved for line segmentation and word segmentation.

References

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Keywords

Segmentation, Optical Character Recognition (OCR), modified horizontal projection profile.