Springer Algorithm & SoC Design for Automotive Vision Systems: For Smart Safe Driving System

An emerging trend in the automobile industry is its convergence with information technology (IT). Indeed, it has been estimated that almost 90% of new automobile technologies involve IT in some form. Smart driving technologies that improve safety as well as green fuel technologies are quite representative of the convergence between IT and automobiles. The smart driving technologies include three key elements: sensing of driving environments, detection of objects and potential hazards and the generation of driving control signals including warning signals. Although radar-based systems are primarily used for sensing the driving environments, the camera has gained importance in advanced driver assistance systems (ADAS). This book covers system-on-a-chip (SoC) designs―including both algorithms and hardware―related with image sensing and object detection by using the camera for smart driving systems. It introduces a variety of algorithms such as lens correction, super resolution, image enhancement and object detections from the images captured by low-cost vehicle camera. This is followed by implementation issues such as SoC architecture, hardware accelerator, software development environment and reliability techniques for automobile vision systems. This book is aimed for the new and practicing engineers in automotive and chip-design industries to provide some overall guidelines for the development of automotive vision systems. It will also help graduate students understand and get started for the research work in this field. From the Back Cover An emerging trend in the automobile industry is its convergence with information technology (IT). Indeed, it has been estimated that almost 90% of new automobile technologies involve IT in some form. Smart driving technologies that improve safety as well as green fuel technologies are quite representative of the convergence between IT and automobiles. The smart driving technologies include three key elements: sensing of driving environments, detection of objects and potential hazards, and the generation of driving control signals including warning signals. Although radar-based systems are primarily used for sensing the driving environments, the camera has gained importance in advanced driver assistance systems(ADAS). This book covers system-on-a-chip (SoC) designs―including both algorithms and hardware―related with image sensing and object detection by using the camera for smart driving systems. It introduces a variety of algorithms such as lens correction, super resolution, image enhancement, and object detections from the images captured by low-cost vehicle camera. This is followed by implementation issues such as SoC architecture, hardware accelerator, software development environment, and reliability techniques for automobile vision systems. This book is aimed for the new and practicing engineers in automotive and chip-design industries to provide some overall guidelines for the development of automotive vision systems. It will also help graduate students understand and get started for the research work in this field. About the Author Prof. Jaeseok Kim received B.S degree from Yonsei University in Korea, M.S degree from KAIST in Korea and Ph. D degree from RPI, USA in 1988. From 1988 to 1993, he was a member of technical staff at the AT&T Bell Lab., Murray Hill, NJ, USA. He is currently a professor of the electrical and electronic engineering department at Yonsei University, Seoul, Korea. He was the best research achievement professor of year 2006 at Yonsei University and received the best brain award in Korea semiconductor technology area in 2005. He has published more than a hundred refereed papers with five text books in electrical engineering area. He holds 45 patents and transferred 5 patents to ten companies. He is now serving as a distinguished lecturer of IEEE Circuit & System society. His current research interests include wi