3 credits
Spring 2026 Lecture Upper Division
Introduction to machine vision and learning algorithms from a human-machine interaction standpoint, and application of machine vision techniques to the design of human-integrated cybernetic systems, such as, robotic systems, flexible automation, and wearable electronics.
Learning Outcomes1Analyze and write computer programs to analyze images for tasks such as filtering, edge detection, segmentation, object recognition, and template matching.
2Describe and use image filtering methods for image processing.
3Describe and use edge detection methods for image processing.
4Use morphological operations to perform shape recognition and template matching.
5Use optical flow methods to study motion.
6Apply techniques for object tracking and motion detection to analyze multiple images or video.
7Apply learning methods such as neural networks, clustering, and linear regression for object recognition.
8Apply a computer vision technique to the control of a robotic arm.
9Plan and develop a working prototype machine vision interface.
Prerequisites
Restrictions
made by Purdue students.