What Is Embedded Vision?
Embedded vision involves the application of image processing and computer vision to embedded systems. Key components of the embedded vision development workflow include algorithm design, system modeling, collaboration, and deployment of vision algorithms.
Use MATLAB Coder to generate C and C++ code for vision algorithms developed in MATLAB. Integrate optimized libraries such as the ARM® Compute Library for ARM architectures and MKL-DNN library for Intel® CPUs.
Targeting FPGAs and ASICs
Use HDL Coder to generate Verilog and VHDL code from vision algorithms that you design using Simulink and Vision HDL Toolbox for FPGA- and ASIC-based platforms.
Testing and Verification
Perform rapid prototyping, processor-in-the-loop (PIL) simulations, and hardware-in-the-loop (HIL) simulations with HDL Verifier, Simulink Real-Time, Embedded Coder, and Simulink Desktop Real-Time to efficiently test and verify your generated code.
Connecting to Embedded Hardware and Deploying
Choose from a variety of hardware support packages for popular embedded hardware to jumpstart receiving and sending real-world data between MATLAB and Simulink, and automatically generate executables from your algorithms to run on embedded hardware platforms.
Real-World Embedded Vision Applications
Learn how MATLAB and Simulink users have developed and deployed real-world embedded vision systems
Continental (21:46) uses MATLAB to: automate learning different traffic sign types, access databases, generate synthetic sign samples, generate code, and monitor and evaluate classifier training using interactive apps.
Clearpath Robotics engineers use MATLAB to prototype algorithms and to analyze and visualize data for industrial robotics research and development.