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on
1
Intro
2
Outline
3
Origins of Edges
4
Types of edges
5
Why edge detection?
6
Closeup of edges
7
Characterizing edges
8
Intensity profile
9
With a little Gaussian noise
10
Effects of Noise
11
Solution: smooth first
12
Derivative theorem of convolution
13
Solution: Smoothing
14
Evaluate Edge Detection
15
Design Criteria for Edge Detection
16
45 years of boundary detection
17
Prewitt and Sobel Edge Detector
Description:
Explore edge detection techniques in computer vision through this comprehensive lecture from the University of Central Florida's CAP5415 course. Delve into the origins and types of edges, understanding their importance in image processing. Examine intensity profiles and the effects of Gaussian noise on edge detection. Learn about smoothing techniques and the derivative theorem of convolution as solutions to noise-related challenges. Evaluate various edge detection methods, including the Prewitt and Sobel edge detectors, while considering design criteria for effective edge detection algorithms. Gain insights into the evolution of boundary detection over 45 years of research and development in the field of computer vision.

Computer Vision: Edge Detection Techniques - Part 1 - Lecture 4

University of Central Florida
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