Abstract
A method for the recognition of handwritten Hindi numerals is proposed based on structural descriptors of numeral shapes. 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 developed to segment the scanned numeral 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) of the scanned numeral. Finally, the syntactic representation is matched against a set of syntactic representation prototypes of handwritten numerals and the recognition result is reported. Early experimental results are encouraging and prove the tolerance of the proposed system to recognize a high variability of numeral shapes.
| Original language | English |
|---|---|
| Pages (from-to) | 983-988 |
| Number of pages | 6 |
| Journal | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |
| Volume | 2 |
| Publication status | Published - 1997 |
| Externally published | Yes |
| Event | Proceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics. Part 3 (of 5) - Orlando, FL, USA Duration: Oct 12 1997 → Oct 15 1997 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Hardware and Architecture