Arabic Character Extraction and Recognition
using Traversing Approach
Abdul Khader Saudagar and Habeeb Mohammed
Abstract: 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 East-South 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.
Keywords: Accuracy, arabic optical character
recognition and text extraction.