Open AccessNumeral Recognition Using Statistical Methods Comparison Study
Author(s) -
Baghdad Science Journal
Publication year - 2011
Publication title -
mağallaẗ baġdād li-l-ʿulūm
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.167
H-Index - 6
eISSN - 2411-7986
pISSN - 2078-8665
DOI - 10.21123/bsj.8.1.188-196
Subject(s) - numeral system , pattern recognition (psychology) , discriminant function analysis , artificial intelligence , linear discriminant analysis , computer science , arabic , character (mathematics) , arabic numerals , mathematics , machine learning , linguistics , philosophy , geometry
The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.