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Computer Vision for Student Competitions: Matching Image Features

version (4.28 MB) by MathWorks Student Competitions Team
Matching Image Features (Chapter 3): Computer Vision Training for Student Competition Teams


Updated 12 Oct 2017

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Learn to detect features using a variety of detectors. We will then show how to match features between images.

Features are points or areas of unique content such as corners or blobs. The Computer Vision System Toolbox™ provides the FAST, Harris, and Shi & Tomasi methods for detecting corner features, and the SURF and MSER methods for detecting blob features.

Features are used in two fundamental ways:
* To localize anchor points for use in image stitching, 3-D reconstruction, and stereovision rectification.
* To represent image contents compactly for object detection, recognition or tracking, without requiring image segmentation.
By learning feature detection and matching, you’ll have the fundamental concepts necessary to perform basic object detection and recognition with features.

Cite As

MathWorks Student Competitions Team (2021). Computer Vision for Student Competitions: Matching Image Features (, GitHub. Retrieved .

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