Opencv-python (11)--Image edge detection

I. Introduction to Functions 1, Laplacian operator function prototypes: Laplacian (SRC, ddepth, Dst=none, Ksize=none, Scale=none, Delta=none, Bordertype=none) SRC: Image matrix ddepth: Depth type 2, Sobel operator function prototype: Sobel (SRC, ddepth, dx, dy, Dst=none, Ksize=none, Scale=none, Delta=none, bordertype= None) src: Image matrix ddepth: Depth type dx:x direction dy:y Direction 3, Canny operator function prototype: Canny (image, Threshold1, Threshold2, Edges=none, aperturesize= None, L2gradient=none) Image: Image matrix Threshold1: Threshold value 1threshold1: Threshold 22, instance Walkthrough 1, Laplace Edge detection code as follows:

#encoding: Utf-8##laplacian边缘检测#Import NumPy as Npimport cv2image = Cv2. Imread("H:\\img\\lena.jpg") image = Cv2. Cvtcolor(Image,cv2. COLOR_bgr2gray)#将图像转化为灰度图像Cv2. Imshow("Original", image) Cv2. Waitkey()#拉普拉斯边缘检测Lap = Cv2. Laplacian(Image,cv2. CV_64f)#拉普拉斯边缘检测Lap = NP. UINT8 (NP. Absolute(lap))# #对lap去绝对值Cv2. Imshow("Laplacian", lap) Cv2. Waitkey()

The results are as follows: Original image:

Laplacian Edge Detection results:

2. Soble Edge Detection code is as follows:

#encoding: Utf-8##Sobel边缘检测#Import NumPy as Npimport cv2image = Cv2. Imread("H:\\img\\lena.jpg") image = Cv2. Cvtcolor(Image,cv2. COLOR_bgr2gray)#将图像转化为灰度图像Cv2. Imshow("Original", image) Cv2. Waitkey()#Sobel边缘检测Sobelx = Cv2. Sobel(Image,cv2. CV_64f,1,0)#x方向的梯度sobely = Cv2. Sobel(Image,cv2. CV_64f,0,1)#y方向的梯度SOBELX = NP. UINT8 (NP. Absolute(SOBELX))#x方向梯度的绝对值sobely = NP. UINT8 (NP. Absolute(sobely))#y方向梯度的绝对值sobelcombined = Cv2. Bitwise_or (sobelx,sobely)#Cv2. Imshow("Sobel X", Sobelx) Cv2. Waitkey() Cv2. Imshow("Sobel Y", sobely) Cv2. Waitkey() Cv2. Imshow("Sobel Combined", sobelcombined) Cv2. Waitkey()

The results are as follows: Original image:

X-Direction Edge detection results:

Y-Direction edge detection results:

XY direction combined with edge detection results:

3. Canny edge detection code is as follows:

#encoding: Utf-8##Canny边缘检测#Import NumPy as Npimport cv2image = Cv2. Imread("H:\\img\\lena.jpg")#读入图像Image = Cv2. Cvtcolor(Image,cv2. COLOR_bgr2gray)#将图像转化为灰度图像Cv2. Imshow("Image", image)#显示图像Cv2. Waitkey()#Canny边缘检测Canny = Cv2. Canny(Image, -, Max) Cv2. Imshow("Canny", canny) Cv2. Waitkey()

The results are as follows: Original image:

Canny Edge detection results:

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Opencv-python (11)--Image edge detection