Arabic Character Extraction and Recognition using Traversing Approach

The intention behind this research is to present an original work undertaken for Arabic character extraction and recognition for attaining higher percentage of recognition rate. Copious techniques for character, text extraction were proposed in earlier decades, but very few of them shed light on Arabic character set. From literature survey, it was found that 100% recognition rate is not attained by earlier proposed implementations. The proposed technique is novel and is based on traversing of the characters in a given text and marking their directions viz. North-South (NS), East-West (EW), North EastSouth West (NE-SW), North West-South East (NW-SE) etc., in an array and comparing them with the pre-defined codes of every character in the dataset. The experiments were conducted on Arabic news videos, documents taken from Arabic Printed Text Image (APTI) database and the results achieved from this research are very promising with a recognition rate of 98.1%. The proposed algorithm in this research work can replace the existing algorithms used in present Arabic Optical Character Recognition (AOCR) systems.