Recognition of handwritten Hindu numerals using structural descriptors
Ashraf Elnagar, Saad Harous · Journal of Experimental & Theoretical Artificial Intelligence · 2003
A method for recognizing handwritten Hindi numerals is proposed based on the structural descriptors of a numeral's shape. The method consists of three major steps. The first one is preprocessing, where a handwritten numeral is scanned, normalized and then thinned. Next, a robust algorithm is used to segment the scanned image into stroke(s), based on feature points, and to identify cavity features. The output of this algorithm is a syntactic representation (that is one or more syntactic terms). Finally, this syntacytic representation is matched against the set of prototype syntactic representations of handwritten numerals for a possible match. Early experimental results are not only encouraging but also proving the tolerance of the proposed system to recognize a high variability of Hindi numerals' shapes. The system attained a successful recognition rate of 96%.