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OpenCV 3 Computer Vision Application Programming Cookbook

You're reading from   OpenCV 3 Computer Vision Application Programming Cookbook Recipes to make your applications see

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Product type Paperback
Published in Feb 2017
Publisher
ISBN-13 9781786469717
Length 474 pages
Edition 3rd Edition
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Author (1):
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Robert Laganiere Robert Laganiere
Author Profile Icon Robert Laganiere
Robert Laganiere
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Table of Contents (15) Chapters Close

Preface 1. Playing with Images FREE CHAPTER 2. Manipulating Pixels 3. Processing the Colors of an Image 4. Counting the Pixels with Histograms 5. Transforming Images with Morphological Operations 6. Filtering the Images 7. Extracting Lines, Contours, and Components 8. Detecting Interest Points 9. Describing and Matching Interest Points 10. Estimating Projective Relations in Images 11. Reconstructing 3D Scenes 12. Processing Video Sequences 13. Tracking Visual Motion 14. Learning from Examples

Eroding and dilating images using morphological filters


Erosion and dilation are the most fundamental morphological operators. Therefore, we will present them in this first recipe. The fundamental component in mathematical morphology is the structuring element. A structuring element can be simply defined as a configuration of pixels (the square shape in the following figure) on which an origin is defined (also called an anchor point). Applying a morphological filter consists of probing each pixel of the image using this structuring element. When the origin of the structuring element is aligned with a given pixel, its intersection with the image defines a set of pixels on which a particular morphological operation is applied (the nine shaded pixels in the following figure). In principle, the structuring element can be of any shape, but most often, a simple shape such as a square, circle, or diamond with the origin at the center is used. Custom structuring elements can be useful to emphasize...

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