Recent advancements in artificial intelligence (AI) have significantly transformed the fields of image processing and computer vision. As traditional techniques give way to more intelligent, data-driven methods, it is essential to explore how this progression shapes research and application across domains. The integration of deep learning, transformers, and generative AI into visual analysis has not only enhanced performance but also broadened the scope of computer vision. There is a fundamental need for a comprehensive resource that bridges classical image processing with modern AI-based techniques.
Advances in the Progression of Image Processing to Computer Vision provides relevant theoretical foundations and the latest empirical insights into the evolution of image processing into modern computer vision. By bridging foundational concepts with advanced vision systems and real-world applications, this book serves as a timely and valuable reference that supports innovation and informed practice across academia, research, and industry. Covering topics such as computer vision techniques and applications, medical image processing, and fitness exercise monitoring and analysis, this book is a critical academic resource for graduate and doctoral students, researchers, and industry professionals in computer vision, image processing, artificial intelligence and more.