opencv sobel robert prewitt canny算子

原理详解请查看另一篇文章

Canny

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

img = cv2.imread('/Users/。。。/Desktop/test.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('canny Image'), plt.xticks([]), plt.yticks([])

plt.show()

Prewitt

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

img = cv2.imread('/Users/panhaokang/Desktop/test.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

img_gaussian = cv2.GaussianBlur(gray,(3,3),0)

kernelx = np.array([[1,1,1],[0,0,0],[-1,-1,-1]])
kernely = np.array([[-1,0,1],[-1,0,1],[-1,0,1]])

img_prewittx = cv2.filter2D(img_gaussian, -1, kernelx)
img_prewitty = cv2.filter2D(img_gaussian, -1, kernely)



plt.subplot(2,2,1),plt.imshow(img,cmap = 'gray')
plt.title('Original'), plt.xticks([]), plt.yticks([])
plt.subplot(2,2,2),plt.imshow(img_prewittx + img_prewitty,cmap = 'gray')
plt.title('prewitt'), plt.xticks([]), plt.yticks([])
plt.subplot(2,2,3),plt.imshow(img_prewittx,cmap = 'gray')
plt.title('prewitt X'), plt.xticks([]), plt.yticks([])
plt.subplot(2,2,4),plt.imshow(img_prewitty,cmap = 'gray')
plt.title('prewitt Y'), plt.xticks([]), plt.yticks([])

plt.show()

sobel

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

# loading image
#img0 = cv2.imread('SanFrancisco.jpg',)
img0 = cv2.imread('/Users/panhaokang/Desktop/test.jpg',)

# converting to gray scale
gray = cv2.cvtColor(img0, cv2.COLOR_BGR2GRAY)

# remove noise
img = cv2.GaussianBlur(gray,(3,3),0)

# convolute with proper kernels
laplacian = cv2.Laplacian(img,cv2.CV_64F)
sobelx = cv2.Sobel(img,cv2.CV_64F,1,0,ksize=5)  # x
sobely = cv2.Sobel(img,cv2.CV_64F,0,1,ksize=5)  # y

plt.subplot(2,2,1),plt.imshow(img,cmap = 'gray')
plt.title('Original'), plt.xticks([]), plt.yticks([])
plt.subplot(2,2,2),plt.imshow(laplacian,cmap = 'gray')
plt.title('Laplacian'), plt.xticks([]), plt.yticks([])
plt.subplot(2,2,3),plt.imshow(sobelx,cmap = 'gray')
plt.title('Sobel X'), plt.xticks([]), plt.yticks([])
plt.subplot(2,2,4),plt.imshow(sobely,cmap = 'gray')
plt.title('Sobel Y'), plt.xticks([]), plt.yticks([])

plt.show()

Robert

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

img = cv2.imread('/Users/panhaokang/Desktop/test.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

img_gaussian = cv2.GaussianBlur(gray,(3,3),0)

kernelx = np.array([[-1,0],[0,1]])
kernely = np.array([[0,-1],[1,0]])

img_robertx = cv2.filter2D(img_gaussian, -1, kernelx)
img_roberty = cv2.filter2D(img_gaussian, -1, kernely)



plt.subplot(2,2,1),plt.imshow(img,cmap = 'gray')
plt.title('Original'), plt.xticks([]), plt.yticks([])
plt.subplot(2,2,2),plt.imshow(img_robertx + img_roberty,cmap = 'gray')
plt.title('robert'), plt.xticks([]), plt.yticks([])
plt.subplot(2,2,3),plt.imshow(img_robertx,cmap = 'gray')
plt.title('robert X'), plt.xticks([]), plt.yticks([])
plt.subplot(2,2,4),plt.imshow(img_roberty,cmap = 'gray')
plt.title('robert Y'), plt.xticks([]), plt.yticks([])

plt.show()