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.
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