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Lära Edge Detection | Image Processing with OpenCV
Computer Vision Course Outline
course content

Kursinnehåll

Computer Vision Course Outline

Computer Vision Course Outline

1. Introduction to Computer Vision
2. Image Processing with OpenCV
3. Convolutional Neural Networks
4. Object Detection
5. Advanced Topics Overview

book
Edge Detection

Edge Detection

Edges represent sudden changes in pixel intensity, which usually correspond to object boundaries. Detecting edges helps in shape recognition and segmentation.

Sobel Edge Detection

The Sobel operator calculates gradients (changes in intensity) in both the X and Y directions, helping detect horizontal and vertical edges.

Canny Edge Detection

The Canny Edge Detector is a multi-stage algorithm that provides more accurate edges by:

  1. Applying Gaussian blur to remove noise.
  2. Finding intensity gradients using Sobel filters.
  3. Suppressing weak edges.
  4. Using double thresholding and edge tracking.

A comparison of edge detection methods:

Uppgift

Swipe to start coding

Apply both methods, Sobel and Canny:

  • Convert photo to grayscale;
  • Apply Sobel filter on X and Y directions with output depth cv2.CV_64F and kernel size 3;
  • Combine Sobel-filtered directions;
  • Apply a Canny filter with a threshold from 200 to 300.

Lösning

Switch to desktopByt till skrivbordet för praktisk övningFortsätt där du är med ett av alternativen nedan
Var allt tydligt?

Hur kan vi förbättra det?

Tack för dina kommentarer!

Avsnitt 2. Kapitel 7
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book
Edge Detection

Edge Detection

Edges represent sudden changes in pixel intensity, which usually correspond to object boundaries. Detecting edges helps in shape recognition and segmentation.

Sobel Edge Detection

The Sobel operator calculates gradients (changes in intensity) in both the X and Y directions, helping detect horizontal and vertical edges.

Canny Edge Detection

The Canny Edge Detector is a multi-stage algorithm that provides more accurate edges by:

  1. Applying Gaussian blur to remove noise.
  2. Finding intensity gradients using Sobel filters.
  3. Suppressing weak edges.
  4. Using double thresholding and edge tracking.

A comparison of edge detection methods:

Uppgift

Swipe to start coding

Apply both methods, Sobel and Canny:

  • Convert photo to grayscale;
  • Apply Sobel filter on X and Y directions with output depth cv2.CV_64F and kernel size 3;
  • Combine Sobel-filtered directions;
  • Apply a Canny filter with a threshold from 200 to 300.

Lösning

Switch to desktopByt till skrivbordet för praktisk övningFortsätt där du är med ett av alternativen nedan
Var allt tydligt?

Hur kan vi förbättra det?

Tack för dina kommentarer!

Avsnitt 2. Kapitel 7
Switch to desktopByt till skrivbordet för praktisk övningFortsätt där du är med ett av alternativen nedan
Vi beklagar att något gick fel. Vad hände?
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