Vision Processing for FPGA, Part 2: Workflow from a Frame-Based Algorithm to a Pixel-Streaming Implementation

From the series: Vision Processing for FPGA

Simulink^® and Vision HDL Toolbox™ help you model hardware implementations of vision processing algorithms. Often these algorithms are written and tested in MATLAB^®. Learn how to reuse your MATLAB work to test and check the results of the Simulink hardware implementation. Details include:

Using MATLAB, Automated Driving Toolbox™, and Computer Vision Toolbox™ to develop and test a lane detection algorithm
Passing data between MATLAB and Simulink using workspace variables
Converting the frame-based input to streaming pixels using the Frame-to-Pixels block, which automatically converts sample rates
Setting up and running the Simulink hardware implementation from the MATLAB script
Comparing the results from the hardware implementation versus the reference algorithm