RoboNation Resources
- Algorithm Design
- Acoustic Processing
- Image Processing and Computer Vision
- Point Cloud
- Mobile Robotics
Image Processing and Computer Vision
Introduction
Most unmanned vehicle systems use image processing and computer vision to interpret their environments. MathWorks tools provide a single environment to design, simulate, and deploy image processing and computer vision algorithms for robotics applications. The toolboxes have a wide variety of algorithms available. MATLAB syntax for image processing and computer vision functionality is compact and efficient, leading to quicker algorithm development. Simulink integration with Model-Based Design and hardware targeting functionality allows the user to design, simulate, and deploy robotics applications quickly.
Examples
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Connectivity, Thresholding, and Blob Detection
- Learn how to read vision data from a webcam on a desktop computer, perform basic thresholding and find blobs within a binary mask
- View the module from the Getting Started Guide "Getting Started with MATLAB and Simulink to Control an Autonomous Vehicle"
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Target Identification
Tools
- Image Processing: perform image analysis, image segmentation, image enhancement, noise reduction, geometric transformations, and image registration
- Computer Vision: perform object detection and tracking, feature detection and extraction, feature matching, stereo vision, camera calibration, and motion detection
- Image Acquisition: acquire images and video from cameras and frame grabbers directly into MATLAB and Simulink
