Video and Webinar Series

Vision Processing for FPGA

This series of videos will show you how to adapt your image and video processing algorithms to target an FPGA using a lane detection system as an example. Learn about the techniques used by our leading customers:

  • Adapting frame-based algorithms to operate on a stream of bits
  • A workflow to verify a streaming hardware implementation against a frame-based algorithm
  • Specific techniques used in the Vision HDL Toolbox lane detection example
  • Targeting the FPGA fabric of a System-on-Chip (SoC) device

Part 1: Vision Processing FPGA and ASIC Hardware Considerations Learn about some of the key factors to consider when targeting a vision processing algorithm to FPGA or ASIC hardware.

Part 2: Workflow from a Frame-Based Algorithm to a Pixel-Streaming Implementation Reuse MATLAB vision processing scripts and algorithms to verify a Simulink hardware implementation.

Part 3: Hardware Design of a Lane Detection Algorithm Learn about the hardware implementation techniques used in the Vision HDL Toolbox lane detection example.

Part 4: Targeting a Lane Detection Design to a Xilinx Zynq Device Generate optimized fixed-point HDL to target the lane detection example to FPGA fabric.

Part 5: Hardware-Software Prototyping of a Lane Detection Design Prototype a hardware-software implementation of an automated driving application using the Computer Vision System Toolbox Support Package for Xilinx Zynq-Based Hardware.