Abstract: Handwritten Kannada Character Recognition has been a challenging research domain due to its diverse applicable environment. Handwriting has always been and will possibly continue to be a means of communication. There is a need to convert these handwritten documents into an editable format which can be achieved by Handwritten Character Recognition Systems. This considerably reduces the storage space required. In this paper focus is on offline handwritten kannada characters. Feature extraction is performed using zoning method together with the concept of euler number. This increases accuracy and speed of recognition as the search space can be reduced.
Keywords: Aspect Ratio, Euler Number, End Points, Offline Handwritten Character Recognition, Zoning.
Title: Offline Handwritten Kannada Character Segmentation and Recognition based on Zoning
Author: Ms. Roopa Tonashyal, Mr. Y. C. Kiran
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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