Title of article :
Numeral Recognition Using Statistical Methods Comparison Study
Author/Authors :
Rasheed, Huda A. AL- Mustansiriyah University - College of sciences - Department of Mathematics, Iraq , Rasheed, Nada A. Babylon University - College of Computer Science, Iraq
Abstract :
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.
Keywords :
Numeral , Recognition , Discriminant
Journal title :
Baghdad Science Journal
Journal title :
Baghdad Science Journal