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.

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.

In an era marked by unprecedented volumes of data generated from various sources, the field of Big Data has emerged as a critical enabler of innovation, decision-making, and competitive advantage across industries. This article explores the advancements in Big Data technologies, methodologies, and applications, highlighting their transformative impact on data analytics, business intelligence, and scientific discovery. From data collection and storage to processing and analysis, Big Data solutions offer scalable, efficient, and cost-effective means to unlock actionable insights from complex and heterogeneous datasets. Through case studies and real-world examples, this article demonstrates the value of Big Data in driving informed decision-making, optimizing operations, and driving innovation in diverse domains, including healthcare, finance, marketing, and cybersecurity. Furthermore, it examines emerging trends and future directions in the field, such as machine learning, artificial intelligence, edge computing, and ethical considerations, shaping the evolution of Big Data and its role in shaping the digital economy and society.