NDLI: Improved recognition of aged Kannada documents by effective segmentation of merged characters

Content Provider	IEEE Xplore Digital Library
Author	Madhavaraj, A. Ramakrishnan, A.G. Shiva Kumar, H.R. Bhat, N.
Copyright Year	2014
Description	Author affiliation: Dept. of Electr. Eng., Indian Inst. of Sci., Bangalore, India (Madhavaraj, A.; Ramakrishnan, A.G.; Shiva Kumar, H.R.) \|\| Dept. of Electron. & Commun., Birla Inst. of Technol., Ranchi, India (Bhat, N.)
Abstract	In optical character recognition of very old books, the recognition accuracy drops mainly due to the merging or breaking of characters. In this paper, we propose the first algorithm to segment merged Kannada characters by using a hypothesis to select the positions to be cut. This method searches for the best possible positions to segment, by taking into account the support vector machine classifier's recognition score and the validity of the aspect ratio (width to height ratio) of the segments between every pair of cut positions. The hypothesis to select the cut position is based on the fact that a concave surface exists above and below the touching portion. These concave surfaces are noted down by tracing the valleys in the top contour of the image and similarly doing it for the image rotated upside-down. The cut positions are then derived as closely matching valleys of the original and the rotated images. Our proposed segmentation algorithm works well for different font styles, shapes and sizes better than the existing vertical projection profile based segmentation. The proposed algorithm has been tested on 1125 different word images, each containing multiple merged characters, from an old Kannada book and 89.6% correct segmentation is achieved and the character recognition accuracy of merged words is 91.2%. A few points of merge are still missed due to the absence of a matched valley due to the specific shapes of the particular characters meeting at the merges.
Starting Page	1
Ending Page	6
File Size	405206
Page Count	6
File Format	PDF
e-ISBN	9781479946655
DOI	10.1109/SPCOM.2014.6983951
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-22
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis aspect ratio Image recognition vertical projection profile segmentation path Character recognition Optical character recognition software matched valleys Support vector machines Image segmentation optical character recognition support vector machine Kannada Feature extraction recognition based segmentation merged character segmentation recognition score OCR
Content Type	Text
Resource Type	Article

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