Design for Embedded Image Processing on FPGAs

Donald G Bailey is Associate Professor in the Institute of Information Sciences and 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.

Preface. Acknowledgements. 1 Image Processing. 1.1 Basic Definitions. 1.2 Image Formation. 1.3 Image Processing Operations. 1.4 Example Application. 1.5 Real-Time Image Processing. 1.6 Embedded Image Processing. 1.7 Serial Processing. 1.8 Parallelism. 1.9 Hardware Image Processing Systems. 2 Field Programmable Gate Arrays. 2.1 Programmable Logic. 2.2 FPGAs and Image Processing. 2.3 Inside an FPGA. 2.4 FPGA Families and Features. 2.5 Choosing an FPGA or Development Board. 3 Languages. 3.1 Hardware Description Languages. 3.2 Software-Based Languages. 3.3 Visual Languages. 3.4 Summary. 4 Design Process. 4.1 Problem Specification. 4.2 Algorithm Development. 4.3 Architecture Selection. 4.4 System Implementation. 4.5 Designing for Tuning and Debugging. 5 Mapping Techniques. 5.1 Timing Constraints. 5.2 Memory Bandwidth Constraints. 5.3 Resource Constraints. 5.4 Computational Techniques. 5.5 Summary. 6 Point Operations. 6.1 Point Operations on a Single Image. 6.2 Point Operations on Multiple Images. 6.3 Colour Image Processing. 6.4 Summary. 7 Histogram Operations. 7.1 Greyscale Histogram. 7.2 Multidimensional Histograms. 8 Local Filters. 8.1 Caching. 8.2 Linear Filters. 8.3 Nonlinear Filters. 8.4 Rank Filters. 8.5 Colour Filters. 8.6 Morphological Filters. 8.7 Adaptive Thresholding. 8.8 Summary. 9 Geometric Transformations. 9.1 Forward Mapping. 9.2 Reverse Mapping. 9.3 Interpolation. 9.4 Mapping Optimisations. 9.5 Image Registration. 10 Linear Transforms. 10.1 Fourier Transform. 10.2 Discrete Cosine Transform. 10.3 Wavelet Transform. 10.4 Image and Video Coding. 11 Blob Detection and Labelling. 11.1 Bounding Box. 11.2 Run-Length Coding. 11.3 Chain Coding. 11.4 Connected Component Labelling. 11.5 Distance Transform. 11.6 Watershed Transform. 11.7 Hough Transform. 11.8 Summary. 12 Interfacing. 12.1 Camera Input. 12.2 Display Output. 12.3 Serial Communication. 12.4 Memory. 12.5 Summary. 13 Testing, Tuning and Debugging. 13.1 Design. 13.2 Implementation. 13.3 Tuning. 13.4 Timing Closure. 14 Example Applications. 14.1 Coloured Region Tracking. 14.2 Lens Distortion Correction. 14.3 Foveal Sensor. 14.4 Range Imaging. 14.5 Real-Time Produce Grading. 14.6 Summary. References. Index.