Authors : Fryal Al-Razaq, Safa Al-Murieb and Sura Mohammed
Abstract: The need to establish powerful Arabic characters recognition becomes high in these days, especially; many Latin character recognition systems reach to high accuracy whereas Arabic ones still lower. The identification of Arabic characters is particularly difficult because the Arabic text has a property of cursive nature which necessitates segmenting the Arabic text into isolated characters, the matter which represents the major challenge for any Arabic character identification system. The goal of this study is to increase the accuracy of Arabic identification systems. This study composes of four phases; the first one is calle d pre-processing to treat some problems that occurs in scanning, the second one is segmentation process phase. This phase involves the challenge area on that system. So, we try in this study to deal with this problem. The third phase is features extraction we try to implement some recognition techniques on the Arabic characters, the last one is identification phase based on the extracted features. In this study, a developed a techniques to detect the skew angle and using different descriptors to recognize the Arabic characters and comparing the accuracy of each one.
Fryal Al-Razaq, Safa Al-Murieb and Sura Mohammed, 2017. Arabic Characters Identification Depending on Extracted Features of the Projection-Based Segmentation. Journal of Engineering and Applied Sciences, 12: 8851-8857.