Abstract

A rotationally invariant optical character recognition system for Sinhala language is developed using Two Dimensional Fourier Transform and Artificial Neural Networks. Sinhala characters of different fonts and font sizes are recognized with over 85% recognition accuracy. Segmentation method based on histogram used in this system gives segmentation accuracy over 70% for complex Sinhala characters.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.