Design for Embedded Image Processing on Fpgas

Introductory material will consider the problem of embedded image processing, and how some of the issues may be solved using parallel hardware solutions. Field programmable gate arrays (FPGAs) are introduced as a technology that provides flexible, finegrained hardware that can readily exploit parallelism within many image processing algorithms. A brief review of FPGA programming languages provides the link between a software mindset normally associated with image processing algorithms, and the hardware mindset required for efficient utilization of a parallel hardware design. The bulk of the book will focus on the design process, and in particular how designing an FPGA implementation differs from a conventional software implementation. Particular attention is given to the techniques for mapping an algorithm onto an FPGA implementation, considering timing, memory bandwidth and resource constraints, and efficient hardware computational techniques. Extensive coverage will be given of a range of image processing operations, discussing efficient implementations and how these may vary according to the application. The techniques will be illustrated with several example applications or case studies from projects or applications I have been involves with. Issues such as interfacing between the FPGA and peripheral devices will be covered briefly, as will designing the system in such a way that it can be more readily debugged and tuned.

Donald G Bailey is Associate Professor in the School of Engineering and Advanced Technology at Massey University, where he leads the Image and Signal Processing Research Group. His research interests include most aspects of image analysis, but in particular the algorithm development process, and training. Bailey has developed a Vision Image Processing System package which has been used in a wide range of image analysis applications. Current and recent projects include: image processing using FPGAs, real time produce grading using machine vision, super-resolution, and sub pixel measurement techniques, camera calibration, and coastal monitoring using automated video analysis. He has been working as an electronics and computer systems engineer in the field of image analysis and machine vision for over 25 years. He began applying FPGA technology to image processing in 2002, and since then has published about 25 papers on issues and applications of FPGAs to image processing.