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Computer Vision for Student Competitions : Automating Image Registration

version (12.3 MB) by MathWorks Student Competitions Team
Automating Image Registration (Chapter 4) : Computer Vision Training for Student Competition Teams

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Updated 12 Oct 2017

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Learn to estimate geometric transforms, apply the transform, and specify image coordinates using panoramic stitching as an example.

You’ll start by performing feature matching between two consecutive images and estimating the geometric transform between two images. The two images will be superimposed onto a larger image to create a super image that encompasses both images. This workflow will be demonstrated on a video of a panning vehicle to create a panoramic image.

Besides learning how to perform image stitching, learning how to estimate geometric transformations enables the user to perform accurate object detection and estimate the motion of an object within a scene.

Cite As

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

Comments and Ratings (2)


the front and back image should have the overlap area, otherwise, the algorithm can‘t get right reuslts.

Melissa Hsieh

MATLAB Release Compatibility
Created with R2015a
Compatible with any release
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