ELEC 474: Machine Vision
Course Work Repositories
The OpenCV library is used using the C++ programming language.
- Labs: https://github.com/tkjsung/ELEC474-Assignment
- Stitching Take-Home Assignment: https://github.com/tkjsung/ELEC474-Lab
Course Info
Text in this section is taken from the website of the Department of Electrical and Computer Engineering at Queen’s University (https://ece.queensu.ca). Text was extracted in 2022.
Computer Vision deals with the automated extraction of information from image and video data. At the low level, techniques such as histogram processing, spatial and frequency-domain filtering, motion segmentation edge extraction, and corner operators are applied as a first step. Follow this, higher level techniques such as geometric primitive extraction, and ultimately object recognition (both model-based and appearance-based) can be applied to determine the identity and accurate location of objects in images. Underlying all of these methods are underlying mathematical concepts such as Principle Component Analysis, Robust Statistics (e.g. RANSAC), and Singular Value Decomposition, as well as optimization methods, such as can be applied to determine least squares solutions to transformations following the Correspondence Problem. Applications of Computer Vision are explored in industrial settings such as automated inspection and recognition. The mathematical basis of stereovision and range vision are presented.