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Segmentation of touching characters in printed Devnagari and Bangla scripts using fuzzy multifactorial analysis

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2 Author(s)
Garain, U. ; Comput. Vision & Pattern Recognition Unit, Indian Stat. Inst., Kolkata, India ; Chaudhuri, B.B.

One of the important reasons for poor recognition rate in optical character recognition (OCR) system is the error in character segmentation. Existence of touching characters in the scanned documents is a major problem to design an effective character segmentation procedure. In this paper, a new technique is presented for identification and segmentation of touching characters. The technique is based on fuzzy multifactorial analysis. A predictive algorithm is developed for effectively selecting possible cut columns for segmenting the touching characters. The proposed method has been applied to printed documents in Devnagari and Bangla: the two most popular scripts of the Indian sub-continent. The results obtained from a test-set of considerable size show that a reasonable improvement in recognition rate can be achieved with a modest increase in computations.

Published in:

Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on  (Volume:32 ,  Issue: 4 )

Date of Publication:

Nov. 2002

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