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Design for Embedded Image Processing on FPGAs by Donald G. Bailey

Design for Embedded Image Processing on FPGAs Donald G. Bailey ebook
Page: 0
ISBN: 0470828498, 9780470828496
Publisher: Wiley-Blackwell
Format: pdf

The hyperspectral image processing system designed by Mercury includes two configurations of its PowerBlock 15 Ultra-Compact Embedded Computers, one for storage and one for image processing. All stages of the design workflow from modeling and simulation, converting the design from a floating-point to a fixed-point representation, automatically generating C code or VHDL/Verilog code for deployment onto DSP or FPGA hardware and verifying the design through real-time simulation on the hardware. The MPPA-256 was designed by Kalray with Global Unichip Corp. -Determining the image processing capabilities of the Raspberry Pi. Various image processing tests have been run on the FPGA platform to demonstrate the functionality of a design that uses 12 parallel processors. Identify a plant model from input-output data, use the identified model to design a controller, and implement the controller on an embedded microprocessor. Title: Design for embedded image processing on FPGAs. The device is aimed at embedded applications in image processing, signal processing, control, communications and data security. Model-Based Design MATLAB image processing and statistical analyses give researchers an objective computational method for measuring the ability of drugs in development to inhibit cancer metastasis. He has also been responsible for the development of various training courses offered by The MathWorks, including “MATLAB® for Image Processing”. Jan 2013 Four Best Practices for Prototyping MATLAB and Simulink Algorithms on FPGAs. The design integrates two configurations of Mercury's PowerBlock® 15 Ultra-Compact Embedded Computers and uniquely combines the processing speed of Intel® Core™ i7 with FPGA capabilities for a real-time sensor interface in an ultra- small form factor. Embedded Computer Vision, exemplified by the migration from powerful workstations to embedded processors in computer vision applications, is a new and emerging field that enables an associated shift in application development and Presents a thorough introductory section on hardware and architectures, design methodologies, and video analytics to aid the reader's understanding through the following chapters. -Get a webcam working with the Raspberry Pi, accessed via python and C (most likely using openCV).