Detect edges using Laplacian operator

Laplacian edge detection uses the Laplacian operator to identify regions of rapid intensity change. 'Laplacian operator' is used to measure the change in the intensity of an image at a pixel.

 

Using cv2.Laplacian method, we can calculate the Laplacian image.

 

Signature

dst = cv2.Laplacian(src, ddepth[, dst[, ksize[, scale[, delta[, borderType]]]]])

Following table summarizes the parameters of Laplacian method.

 

Parameter	Description
src	Source image in which you want to apply Laplacian filter.
ddepth	Specifies the depth of destination image. It specifies the desired data type for the output image, which can be one of the following values:   cv2.CV_8U: 8-bit unsigned integer. cv2.CV_16U: 16-bit unsigned integer. cv2.CV_16S: 16-bit signed integer. cv2.CV_32F: 32-bit floating-point. cv2.CV_64F: 64-bit floating-point.
ksize	It is optional parameter, specifies the size of the kernel (filter) that defines the extent of the Laplacian operation
scale	It is optional parameter, specifies the scale factor for the computed Laplacian values.
delta	It is optional parameter, added to the result.
borderType	It is optional parameter, specifies how border of the image is handled. Following values are supported.   cv2.BORDER_DEFAULT: Default border behavior. cv2.BORDER_CONSTANT: Adds a constant border (specified by borderValue). cv2.BORDER_REFLECT: Reflects the image around the border. cv2.BORDER_REFLECT_101: Reflects the image around the border with a slight change. cv2.BORDER_REPLICATE: Replicates the last pixel of the border.

 

Example

laplacian = cv.Laplacian(gray_scale_image, -1)

The result of Laplacian method might have both positive and negative values, so you convert it to an appropriate data type using cv2.convertScaleAbs to ensure it's in the correct format for display.

 

laplacian = cv.convertScaleAbs(laplacian)

 

Find the below working application.

 

laplacian_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)

laplacian = cv.Laplacian(gray_scale_image, -1)
#laplacian = np.uint8(np.absolute(laplacian))
# Convert the result to the appropriate data type and scale it
laplacian = cv.convertScaleAbs(laplacian)

cv.imshow('Original image', image)
cv.imshow('gray_scale_image', gray_scale_image)
cv.imshow('Laplacian image', laplacian)

cv.waitKey(0)

# Close the OpenCV windows
cv.destroyAllWindows()

Output

Original image

 

Gray scale image

Laplacian image

  

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