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Arabic (Indian) Numeral Handwritten Recognition Using Angular Radial Transform | ||
| Diyala Journal For Pure Science | ||
| Article 1, Volume 13, Issue 2, 2017, Pages 48-64 | ||
| Authors | ||
| Ali Mohammed Sahan; Ali Sami Azeez | ||
| Abstract | ||
| In this paper, an Arabic (Indian) numeral handwritten recognition method is presented based on angular radial transform. The angular radial transform is considered as a global features extraction descriptor in order to provide distinct and rotation invariant features about the images of Arabic numeral handwritten. Also, in this, paper the performance of both angular transform and radial transform is investigated and compared. Hellinger distance measure is adopted in the classification stage to compute the distance between the test and training Arabic numeral handwritten images. The extensive experiments indicate that the proposed approach achieved a high recognition rate of 96.74% which is better of recognition rates achieved using its counterpart's angular and radial transforms which achieved 91.34% and 87.10% respectively. Also, they indicated that the performance of angular transforms is outperforms the performance of radial transform. Furthermore, observed that the proposed method is rotation invariant. | ||
| Keywords | ||
| Numeral handwritten recognition; Angular radial transform; Global features; Rotation invariant features; Hellinger distance measure | ||
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