Design For Embedded Image Processing on Fpgas

The demands of increasingly complex embedded systems and associated performance computations have resulted in the development of heterogeneous computing architectures that often integrate several types of processors, analog and digital electronic components, and mechanical and optical components―all on a single chip.

This book presents a selection of papers representing current research on using field programmable gate arrays (FPGAs) for realising image processing algorithms. These papers are reprints of papers selected for a Special Issue of the Journal of Imaging on image processing using FPGAs. A diverse range of topics is covered, including parallel soft processors, memory management, image filters, segmentation, clustering, image analysis, and image compression. Applications include traffic sign recognition for autonomous driving, cell detection for histopathology, and video compression. Collectively, they represent the current state-of-the-art on image processing using FPGAs.

Build Real-world Image Processing Applications using Python and OpenCV on Raspberry Pi 4/3/2/Zero-For Absolute Beginner.

One of the most significant challenges in the development of embedded and cyber-physical systems is the gap between the disciplines of software and control engineering. In a marketplace, where rapid innovation is essential, engineers from both disciplines need to be able to explore system designs collaboratively, allocating responsibilities to software and physical elements, and analyzing trade-offs between them.

This book provides step-by-step guidance on how to design VLSI systems using Verilog.