OpenCV: Sobel edge detection

Sobel operation is used for edge detection and gradient computation in Image processing.

 

Sobel operation has two 3X3 convolution kernels.

a.   Kernel1 : For detecting changes in intensity in the horizontal (x) direction

b.   Kernel2: For detecting the changes in vertical direction.

 

Horizontal kernel

-1  0  1

-2  0  2

-1  0  1

 

Vertical Kernel

-1 -2 -1

 0  0  0

1     2  1

 

How to find edges using Sobel operator in OpenCV?

Using cv2.Sobel method, we can apply Sobel operator on an Image.

 

Signature

cv2.Sobel(src, ddepth, dx, dy, ksize[, scale[, delta[, borderType]]])

 

Following table summarizes the parameters of Sobel method.

Parameter	Description
src	Specifies the source image on which you want to apply sobel operator.
ddepth	Specifies desired depth of the image. By default it is set to -1 to indicate output image has same depth as source image.
dx	Order of derivatives in x-axis
dy	Order of derivatives in y-axis
ksize	Specifies the size of Sobel kernel. In general it is set to odd number like 3, 5, 7 etc.,
scale	It is an optional parameter used to scale the result
delta	It is an optional parameter, added to the result.
borderType	It is optional parameter, specifies how to handle border pixels.

 

sobel_edge_detection.py

import cv2 as cv
import numpy as np

image = cv.imread('gateway_of_india.png')
gray_scale_image = cv.cvtColor(image, cv.COLOR_BGR2GRAY)

sobel_x = cv.Sobel(image, -1, 1, 0)
sobel_y = cv.Sobel(image, -1, 0, 1)
sobel = cv.bitwise_or(sobel_x, sobel_y)

cv.imshow('Original image', image)
cv.imshow('gray_scale_image', gray_scale_image)
cv.imshow('sobel_x', sobel_x)
cv.imshow('sobel_y', sobel_y)
cv.imshow('sobel', sobel)

cv.waitKey(0)

# Close the OpenCV windows
cv.destroyAllWindows()

 

Output

Original image

 

 

Gray scale image

 

sobel_x

sobel_y

 

 

sobel

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