An Exploratory Review on Text Detection and Recognition in Images and Videos Using Machine Learning and Deep Learning Techniques - Sundar Raj, Keerthana; Savitha, J (International Journal of Computer Sciences and Engineering, 2025)
The increasing reliance on images and videos as sources of information has led to a growing demand for automated text detection and recognition systems. This literature review explores the current advancements in text extraction methodologies, focusing on machine learning and deep learning techniques. Various approaches, including text detection, localization, recognition, and tracking, are discussed alongside the challenges posed by environmental conditions, text alignment, font variations, and background noise. The study highlights applications in license plate recognition, industrial automation, vehicle tracking, and self-navigating automobiles, where text extraction plays a crucial role. Furthermore, a comparative analysis of existing machine learning-based and deep learning-based models is conducted, evaluating their effectiveness in different scenarios. This examination also discusses evaluation metrics used to validate model performance and identifies the computational challenges associated with processing high-resolution images and videos in real-time. The findings emphasize the need for robust mathematical models and optimization techniques to improve the efficiency and accuracy of text recognition system