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March 28, 2021 16:04
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Experimenting with Blur ,Dialte and Gray scale Images
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import cv2 | |
import numpy as np | |
img = cv2.imread("Resources/lena.png") | |
imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) # converting to it gray scale image | |
cv2.imshow("GrayScale", imgGray) | |
# To Blur the image we will use Gaussian Blur to blur | |
imgBlur = cv2.GaussianBlur(imgGray,(7,7),0) # as a paramter kernel size is passed | |
cv2.imshow("GrayScaleBlur", imgBlur) | |
# To detect the edges we use the Canny Filter | |
imgCanny = cv2.Canny(imgGray,150,100) | |
cv2.imshow("Canny_Edge",imgCanny) | |
# Dialate the images | |
# inedge detection we didnt get the thick lines so what we can do is to increase thickness is dialate the image | |
kernel = np.ones((5,5), np.uint8) | |
imgDialted = cv2.dilate(imgCanny,kernel ,iterations=1) | |
cv2.imshow("Dialted Image ", imgDialted) | |
# Erode the image | |
imgEroded=cv2.erode(imgCanny,kernel,iterations=1) | |
cv2.imshow("Eroded Image ", imgCanny) | |
cv2.waitKey(0) |
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