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Canny Edge Detection in Python

This project implements the Canny Edge Detection algorithm in Python using OpenCV and NumPy. Canny Edge Detection is a popular algorithm used in image processing to detect a wide range of edges in images.

Features

  • Grayscale conversion: Converts the input image to a grayscale image.
  • Gaussian blurring: Applies Gaussian blur to the grayscale image to reduce noise.
  • Gradient calculation: Calculates the gradient magnitude and direction of the blurred image using Sobel operators.
  • Non-maximum suppression: Suppresses non-maximum pixels to thin out the edges.
  • Double thresholding: Applies double thresholding to classify edge pixels as strong, weak, or non-edge pixels.
  • Edge tracking by hysteresis: Tracks edges by connecting strong edges and weak edges that are connected to strong edges.