DocumentCode :
317940
Title :
Recognition of handwritten Hindi numerals using structural descriptors
Author :
Elnagar, A. ; Al-Kharousi, F. ; Harous, S.
Author_Institution :
Dept. of Comput. Sci., Sultan Qaboos Univ., Muscat, Oman
Volume :
2
fYear :
1997
fDate :
12-15 Oct 1997
Firstpage :
983
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: 1) preprocessing, where a handwritten numeral is scanned, normalized, and then thinned; 2) a robust algorithm is developed to segment the scanned numeral image into stroke(s), based on feature points; and 3) 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
Keywords :
character recognition; feature extraction; image representation; image segmentation; parallel algorithms; character recognition; feature extraction; feature points; handwritten Hindi numerals; parallel algorithm; preprocessing; segmentation; structural descriptors; syntactic representation; thinning; Character recognition; Computer science; Educational institutions; Handwriting recognition; Image segmentation; Natural languages; Postal services; Robustness; Shape; Text recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
ISSN :
1062-922X
Print_ISBN :
0-7803-4053-1
Type :
conf
DOI :
10.1109/ICSMC.1997.638075
Filename :
638075
Link To Document :
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