Canny Edge Detection

Edge detection is one of the fundamental operations when we perform image processing. It helps us reduce the amount of data (pixels) to process and maintains the structural aspect of the image. We're going to look into many people think it as the ultimate edge detectorm Canny Edge Detection. With this detector, we get clean, thin edges that are well connected to nearby edges.

The canny edge detector is a 4-step detection process. The steps are:

1. Noise Reduction - 5x5 Gaussian filter
2. Calculating gradients - Finding Intensity Gradient of the Image
3. Nonmaximum suppression - upper threshold
4. Thresholding with hysterysis - upper/lower threshold

The details are in Canny Edge Detection.

Here is a code that can do edge detection:

import cv2
import numpy as np
from matplotlib import pyplot as plt

img = cv2.imread('messi5.jpg',0)
edges = cv2.Canny(img,100,200)

plt.subplot(121),plt.imshow(img,cmap = 'gray')
plt.title('Original Image'), plt.xticks([]), plt.yticks([])
plt.subplot(122),plt.imshow(edges,cmap = 'gray')
plt.title('Edge Image'), plt.xticks([]), plt.yticks([])

plt.show()

Images used:

1. Canny Edge Detection

OpenCV 3 Tutorial

image & video processing

OpenCV 3 image and video processing with Python