M.L.M Karunanayaka, N.D Kodikara, G.D.S.P Wimalaratne
Sinhala is the national language of the country of Sri Lanka. 70% of the people living in Sri Lanka use Sinhala language for their day-to-day activities .Very little number of researches have been done about Sinhala handwriting recognition. This proposed system is focused on recognition of Sinhala handwriting using postal city names as a case study .Training and testing of this case study is done by using the handwriting of postal envelops. Therefore this research not limited only to a single writing style. Number of main post offices in Sri Lanka are limited to five hundreds and one. In this system one of the major impediments are touching characters. Segmentation of handwritten touching characters become a crucial step in such systems. Conventional segmentation methods incapable of handling the complexity exists in Sinhala handwritten characters. The proposed method separates touching characters into isolated character models in two steps viz; basic projection profile method and water reservoir concept. Finally recognition process carries with using the Kohenen artificial neural network. Over 300 patterns are tested in segmentation and 92% accuracy was reported and recognition phase was tested using 400 patterns and 84.5% success rate was reported.
In Conference Proceedings - 6th International Information Technology Conference on From Research to Reality, Infotel Lanka Society Colombo, Sri Lanka, 29 Nov- 01 Dec 2004, pp. 23-29, ISBN 955-8974-01-3.