Recognition of Arabic characters
Al-Yousefi, H.
Udpa, S.S.
Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Aug 1992
Volume: 14,
Issue: 8
On page(s): 853-857
ISSN: 0162-8828
References Cited: 20
CODEN: ITPIDJ
INSPEC Accession Number: 4246278
Digital Object Identifier: 10.1109/34.149585
Current Version Published: 2002-08-06
Abstract
A statistical approach for the recognition of Arabic characters is
introduced. As a first step, the character is segmented into primary and
secondary parts (dots and zigzags). The secondary parts of the character
are then isolated and identified separately, thereby reducing the number
of classes from 28 to 18. The moments of the horizontal and vertical
projections of the remaining primary characters are then calculated and
normalized with respect to the zero-order moment. Simple measures of the
shape are obtained from the normalized moments. A 9-D feature vector is
obtained for each character. Classification is accomplished using
quadratic discriminant functions. The approach was evaluated using
isolated, handwritten, and printed characters from a database
established for this purpose. The results indicate that the technique
offers better classification rates in comparison with existing methods
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
