A syntactic PR approach to Telugu handwritten character recognition

This paper shows a character recognition mechanism based on a syntactic PR approach that uses the trie data structure for efficient recognition. It uses approximate matching of the string for classification. During the preprocessing an input character image is transformed into a skeletonized image and discrete curves are found using a 3 x 3 pixel region. A trie, which we call as a sequence trie is used for a look up approach at a lower level to encode a discrete curve pattern of pixels. The sequence of such discrete curves from the input pattern is looked up in the sequence trie. The encoding of several such sequence numbers for the thinned character constructs a pattern string. Approximate string matching is used to compare the encoded pattern string from a template character with the pattern string obtained from the input character. We consider the approximate matching of the string instead of the exact matching to make the approach robust in the presence of noise. Another trie data structure (called pattern trie) is used for the efficient storage and retrieval for approximate matching of the string. We make use of the trie since it takes O(m) in worst case where m is the length of the longest string in the trie. For the approximate string matching we use look ahead with a branch and bound scheme in the trie. Here we apply our method on 43 Telugu characters from the basic Telugu characters for demonstration. The proposed approach has recognised all the test characters given here correctly, however more extensive testing on realistic data is required.