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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

Detecting FAST features at multiple scales


FAST has been introduced as a quick way to detect keypoints in an image. With SURF and SIFT, the emphasis was on designing scale-invariant features. More recently, new interest point detectors have been introduced with the objective of achieving both fast detection and invariance to scale changes. This recipe presents the Binary Robust Invariant Scalable Keypoints (BRISK) detector. It is based on the FAST feature detector that we described in a previous recipe of this chapter. Another detector, called ORB (Oriented FAST and Rotated BRIEF), will also be discussed at the end of this recipe. These two feature point detectors constitute an excellent solution when fast and reliable image matching is required. They are especially efficient when they are used in conjunction with their associated binary descriptors, as will be discussed in Chapter 9, Describing and Matching Interest Points.

How to do it...

Following what we did in the previous recipes, the...

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