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 Toolbox Support Package for Xilinx Zynq-Based Hardware.