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Arabic Handwritten Recognition by using His Features | ||
| Al-Rafidain University College For Sciences | ||
| Article 1, Volume 0, Issue 26, 2017, Pages 69-82 | ||
| Author | ||
| Ali Shaker Mahmood | ||
| Abstract | ||
| The present study is a contribution in the filed of Arabic character recognition. The first step is to enter an image from a scanner, and then some special processes are done on the image like (smoothing and thinning and resizing) before continuous to segmentation phase. Then modified moment invariant computed using the shape boundary of the character only is utilized as features. Also this study is concerned with the recognition of handwritten Arabic character drawn on a graphic tablet. At first feature that are suitable for recognition are proposed. Feature that are found to be independent of the writer style are represented as a list (vector) of integer values. The designed system in general view is an Arabic text recognition system basically includes a segmentation stage in order to recognize handwritten Arabic words. The segmentation process is completely based on tracing the outer of given word and calculating the output distance between the extreme points of intersection of the contour with vertical line. At the output of the segmentation stage the cursive word is presented as a sequence of isolated character contour. | ||
| Keywords | ||
| Recognition | ||
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