Augmented Reality and Ontology-based Approach for Enhancing Arabic Text Recognition and Visualization

Abstract

Written text is a commonly used means of transferring information in our daily lives, and it is especially crucial in unfamiliar environments where we rely on written text to achieve our goals. In such scenarios, signs or signboards help us navigate and determine the direction we should take. However, various factors, such as prolonged exposure to the text, text obstructions, and poor lighting, may hinder our ability to read the text accurately, leading to erroneous readings. A single incorrectly read letter can lead to a false interpretation of the entire text, potentially resulting in serious consequences. To address this issue, we propose an approach to correct letter imperfections in a word and display it in an improved manner. Our approach consists of two phases: the pre-treatment phase and the letter imperfection recovery phase. The pre-treatment phase relies on Augmented Reality technology to detect and recognize text with letter imperfections. In the letter imperfection recovery phase, we employ ontology and a database to correct the letter imperfections. To enhance the accuracy of our results, we apply Augmented Reality technology to obtain a 3D image for perfect visualization. We conducted an evaluation and experimentation phase by administering a questionnaire to a group of participants to obtain feedback on our approach. The results were encouraging and demonstrated the effectiveness of our approach.