Isolated Multifont Arabic Character Recognition Using Fourier Descriptors | ||
| Journal of Al-Nahrain University - Science | ||
| Article 1, Volume 16, Issue 1, March 2013, Pages 176-182 | ||
| Author | ||
| Shatha M. Noor | ||
| Abstract | ||
| Optical Characters Recognition (OCR) has been an active subject of research since the early days of computers. Despite the age of the subject, it remains one of the most challenging and exciting areas of research in computer science. In recent years it has grown into a mature discipline, producing a huge body of work. Arabic character recognition has been one of the last major languages to receive attention. In this paper a simple and accurate method is proposed to recognize isolated Arabic characters using Fourier descriptors feature set and character’s dots information represented by number of dots and their position. Eight commonly used font styles in different font sizes were used in the test, first each font style is tested separately and found the recognition ratio is excellent, then a combination of font styles were tested; and it was found that as more font styles used the recognition ratio decrease. | ||
| Keywords | ||
| Character Recognition; Binarization; thinning; Segmentation; Chain Codes; Fourier Descriptor; Grand Class | ||
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