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Edge Detection - Exploring Boundaries in Computer Vision - cover

Edge Detection - Exploring Boundaries in Computer Vision

Fouad Sabry

Publisher: One Billion Knowledgeable

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Summary

What is Edge Detection
 
Edge detection is a collection of mathematical techniques that are aimed at recognizing edges, which are defined as curves in a digital image at which the brightness of the image changes abruptly or, more formally, contains discontinuities. The difficulty of discovering discontinuities in one-dimensional signals is referred to as step detection, and the problem of finding signal discontinuities over time is referred to as change detection. Both of these techniques are used to find discontinuities in signals. The method of edge detection is an essential tool in the fields of image processing, machine vision, and computer vision, notably in the areas of feature detection and feature extraction.
 
How you will benefit
 
(I) Insights, and validations about the following topics:
 
Chapter 1: Edge detection
 
Chapter 2: Digital image processing
 
Chapter 3: Sobel operator
 
Chapter 4: Roberts cross
 
Chapter 5: Canny edge detector
 
Chapter 6: Marr-Hildreth algorithm
 
Chapter 7: Scale-invariant feature transform
 
Chapter 8: Discrete Laplace operator
 
Chapter 9: Scale space
 
Chapter 10: Prewitt operator
 
(II) Answering the public top questions about edge detection.
 
(III) Real world examples for the usage of edge detection in many fields.
 
Who this book is for
 
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Edge Detection.
Available since: 04/29/2024.
Print length: 120 pages.

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