A Novel Method for Arabic Text Detection with Interactive Visualization

Text detection, recognition, and visualization from natural scenes are considered significant research topics in the field of information and communication technologies. Written text serves as a crucial source of information that humans rely on in their daily lives. However, detecting text poses several challenges, including variations in writing style, color, size, orientation, and complex backgrounds. In this study, we present a comprehensive application named ATDRV, which aims to address these challenges. For text detection and recognition, we propose a real-time multi-oriented text deep fully convolutional network system trained end-to-end. Additionally, we implement a visualization module based on Augmented Reality to display the results more clearly to users. The output of our application is a large and clear 3D object that enables easy reading of the text. Our approach improves the user experience and facilitates the reading of Arabic text regardless of color, orientation, writing style, or complex backgrounds.