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

Course Content

Computer Vision Course Outline

Computer Vision Course Outline

1. Introduction to Computer Vision
2. Image Processing with OpenCV
3. Convolutional Neural Networks

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:

Task

Swipe to start coding

Your task is to apply both methods, Sobel and Canny. Steps:

  • 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.

Solution

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Section 2. Chapter 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:

Task

Swipe to start coding

Your task is to apply both methods, Sobel and Canny. Steps:

  • 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.

Solution

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 2. Chapter 7
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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