While Optical Character Recognition (OCR) techniques have made significant strides, they often fall short when dealing with non-text elements in documents. This gap highlighted the need for comprehensive solutions that recognize text and accurately detect and reconstruct tables and other graphical components. Our collaborative research efforts, extensive experiments, and continuous learning have culminated in developing the algorithms presented in this book, a testament to the power of teamwork in overcoming challenges. The book is structured to provide a thorough understanding of the problem domain, existing techniques, and our proposed solutions. We begin with an introduction to the challenges of digitizing printed documents, highlighting the limitations of current OCR methods and the need for advanced table detection and recognition algorithms. Subsequent chapters delve into detailed surveys of existing techniques, followed by a comprehensive presentation of our algorithms. We also explore the application of our enhanced algorithm in various scenarios, showcasing its robustness and effectiveness.
