Dr Donald Bailey starts with introductory material considering 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, fine-grained 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 design process for implementing an image processing algorithm on an FPGA is compared with that for a conventional software implementation, with the key differences highlighted. 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 is given of a range of low and intermediate level image processing operations, discussing efficient implementations and how these may vary according to the application. The techniques are illustrated with several example applications or case studies from projects or applications he has been involved with. Issues such as interfacing between the FPGA and peripheral devices are covered briefly, as is designing the system in such a way that it can be more readily debugged and tuned. Provides a bridge between algorithms and hardware Demonstrates how to avoid many of the potential pitfalls Offers practical recommendations and solutions Illustrates several real-world applications and case studies Allows those with software backgrounds to understand efficient hardware implementation Design for Embedded Image Processing on FPGAs is ideal for researchers and engineers in the vision or image processing industry, who are looking at smart sensors, machine vision, and robotic vision, as well as FPGA developers and application engineers. The book can also be used by graduate students studying imaging systems, computer engineering, digital design, circuit design, or computer science. It can also be used as supplementary text for courses in advanced digital design, algorithm and hardware implementation, and digital signal processing and applications. Companion website for the book: wiley.com/go/bailey/fpga

Dr Donald Bailey starts with introductory material considering theproblem of embedded image processing, and how some of the issuesmay be solved using parallel hardware solutions. Field programmablegate arrays (FPGAs) are introduced as a technology that providesflexible, fine-grained hardware that can readily exploitparallelism within many image processing algorithms. A brief reviewof FPGA programming languages provides the link between a softwaremindset normally associated with image processing algorithms, andthe hardware mindset required for efficient utilization of aparallel hardware design. The design process for implementing animage processing algorithm on an FPGA is compared with that for aconventional software implementation, with the key differenceshighlighted. Particular attention is given to the techniques formapping an algorithm onto an FPGA implementation, consideringtiming, memory bandwidth and resource constraints, and efficienthardware computational techniques. Extensive coverage is given of arange of low and intermediate level image processing operationsdiscussing efficient implementations and how these may varyaccording to the application. The techniques are illustrated withseveral example applications or case studies from projects orapplications he has been involved with. Issues such as interfacingbetween the FPGA and peripheral devices are covered briefly, as isdesigning the system in such a way that it can be more readilydebugged and tuned.* Provides a bridge between algorithms and hardware* Demonstrates how to avoid many of the potential pitfalls* Offers practical recommendations and solutions* Illustrates several real-world applications and casestudies* Allows those with software backgrounds to understand efficienthardware implementationDesign for Embedded Image Processing on FPGAs is idealfor researchers and engineers in the vision or image processingindustry, who are looking at smart sensors, machine vision, androbotic vision, as well as FPGA developers and applicationengineers.The book can also be used by graduate students studying imagingsystems, computer engineering, digital design, circuit design, orcomputer science. It can also be used as supplementary text forcourses in advanced digital design, algorithm and hardwareimplementation, and digital signal processing and applications.Companion website for the book: href="wiley.com/go/bailey/fpga">wiley.com/go/bailey/fpga

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.