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OpenCV Computer Vision Application Programming Cookbook Second Edition

OpenCV Computer Vision Application Programming Cookbook Second Edition

By : Robert Laganiere
3.7 (3)
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OpenCV Computer Vision Application Programming Cookbook Second Edition

OpenCV Computer Vision Application Programming Cookbook Second Edition

3.7 (3)
By: Robert Laganiere

Overview of this book

OpenCV 3 Computer Vision Application Programming Cookbook is appropriate for novice C++ programmers who want to learn how to use the OpenCV library to build computer vision applications. It is also suitable for professional software developers wishing to be introduced to the concepts of computer vision programming. It can also be used as a companion book in a university-level computer vision courses. It constitutes an excellent reference for graduate students and researchers in image processing and computer vision.
Table of Contents (13 chapters)
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12
Index

Matching local templates


Feature point matching is the operation by which one can put in correspondence points from one image to points from another image (or points from an image set). Image points should match when they correspond to the image of the same scene element (or the object point) in the real world.

A single pixel is certainly not sufficient to make a decision on the similarity of two keypoints. This is why an image patch around each keypoint must be considered during the matching process. If two patches correspond to the same scene element, then one might expect their pixels to exhibit similar values. A direct pixel-by-pixel comparison of pixel patches is the solution presented in this recipe. This is probably the simplest approach to feature point matching, but as we will see, it is not the most reliable one. Nevertheless, in several situations, it can give good results.

How to do it...

Most often, patches are defined as squares of odd sizes centered at the keypoint position....

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