OpenCV--图像的形态学处理

纵饮孤独 提交于 2020-02-10 01:22:30

形态学-腐蚀操作

img = cv2.imread('dige.png')

cv2.imshow('img', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

效果:

kernel = np.ones((3,3),np.uint8) 
erosion = cv2.erode(img,kernel,iterations = 1) #迭代次数

cv2.imshow('erosion', erosion)
cv2.waitKey(0)
cv2.destroyAllWindows()

效果:

pie = cv2.imread('pie.png')

cv2.imshow('pie', pie)
cv2.waitKey(0)
cv2.destroyAllWindows()

效果:

kernel = np.ones((30,30),np.uint8) 
erosion_1 = cv2.erode(pie,kernel,iterations = 1)
erosion_2 = cv2.erode(pie,kernel,iterations = 2)
erosion_3 = cv2.erode(pie,kernel,iterations = 3)
res = np.hstack((erosion_1,erosion_2,erosion_3))
cv2.imshow('res', res)
cv2.waitKey(0)
cv2.destroyAllWindows()

效果:

形态学-膨胀操作

kernel = np.ones((3,3),np.uint8) 
dige_erosion = cv2.erode(img,kernel,iterations = 1)

kernel = np.ones((3,3),np.uint8) 
dige_dilate = cv2.dilate(dige_erosion,kernel,iterations = 1)

cv2.imshow('dilate', dige_dilate)
cv2.waitKey(0)
cv2.destroyAllWindows()
#先腐蚀再膨胀

效果:

pie = cv2.imread('pie.png')

kernel = np.ones((30,30),np.uint8) 
dilate_1 = cv2.dilate(pie,kernel,iterations = 1)
dilate_2 = cv2.dilate(pie,kernel,iterations = 2)
dilate_3 = cv2.dilate(pie,kernel,iterations = 3)
res = np.hstack((dilate_1,dilate_2,dilate_3))
cv2.imshow('res', res)
cv2.waitKey(0)
cv2.destroyAllWindows()

效果:

 开运算与闭运算

# 开:先腐蚀,再膨胀
img = cv2.imread('dige.png')

kernel = np.ones((5,5),np.uint8) 
opening = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel)

cv2.imshow('opening', opening)
cv2.waitKey(0)
cv2.destroyAllWindows()

效果:

# 闭:先膨胀,再腐蚀
img = cv2.imread('dige.png')

kernel = np.ones((5,5),np.uint8) 
closing = cv2.morphologyEx(img, cv2.MORPH_CLOSE, kernel)

cv2.imshow('closing', closing)
cv2.waitKey(0)
cv2.destroyAllWindows()

效果:

 梯度运算

# 梯度=膨胀-腐蚀
pie = cv2.imread('pie.png')
kernel = np.ones((7,7),np.uint8) 
dilate = cv2.dilate(pie,kernel,iterations = 5)
erosion = cv2.erode(pie,kernel,iterations = 5)

res = np.hstack((dilate,erosion))

cv2.imshow('res', res)
cv2.waitKey(0)
cv2.destroyAllWindows()

效果:

gradient = cv2.morphologyEx(pie, cv2.MORPH_GRADIENT, kernel)

cv2.imshow('gradient', gradient)
cv2.waitKey(0)
cv2.destroyAllWindows()

效果:

礼帽与黑帽

礼帽 = 原始输入-开运算结果

黑帽 = 闭运算-原始输入

#礼帽
img = cv2.imread('dige.png')
tophat = cv2.morphologyEx(img, cv2.MORPH_TOPHAT, kernel)
cv2.imshow('tophat', tophat)
cv2.waitKey(0)
cv2.destroyAllWindows()

效果:

#黑帽
img = cv2.imread('dige.png')
blackhat  = cv2.morphologyEx(img,cv2.MORPH_BLACKHAT, kernel)
cv2.imshow('blackhat ', blackhat )
cv2.waitKey(0)
cv2.destroyAllWindows()

效果:

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