In this paper, an effort is made to apply optical character recognition (OCR) for Braille translation on Kannada characters. In general, OCR systems for Indian language are more complex due to larger number of vowels, consonants, and conjuncts and Indian languages are inflectional and agglutinative in nature. Specifically, characters of Kannada script have higher similarity in shape and higher variability across fonts, making recognition of characters a difficult task. A decision tree is developed in this research work. The main motivations are that decision trees provide a natural way to incorporate prior knowledge of domain and many Kannada characters have similar looking shapes. The similar looking characters can be grouped and then further partitioned into categories at various levels to effectively create a decision tree. To facilitate this, three modular classifiers are developed based on the nature of Kannada characters. These modular classifiers are employed at nodes of the decision tree. The Braille equivalent of Kannada characters is obtained by translation rules. An overall accuracy of classification and Braille translation of 93.80% is obtained.
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Computer Science Applications
- Computer Graphics and Computer-Aided Design