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OpenCV四) —— 图像形态学处理(腐蚀操作膨胀操作开运算与闭运算梯度运算礼貌与黑帽)

news 来源：原创 2024/5/17 13:16:56

图像形态学处理

腐蚀操作 cv2.erode()

用腐蚀操作就能够去掉这些毛刺

毛刺都没有了，线条变细了

#形态学-腐蚀操作
img = cv2.imread('dige.png')

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

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

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

iteration改成2、3就更细了

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

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

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()

膨胀操作 cv2.dilate()

膨胀操作可以让变细的线条变粗，和腐蚀操作是互为逆操作的

腐蚀是在这种混合的情况下都变黑，而膨胀是在这种情况下都变白

#形态学-膨胀操作
img = cv2.imread('dige.png')
cv2.imshow('img', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

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

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

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()

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()

开运算与闭运算 cv2.morphologyEx()

开：先腐蚀再膨胀

闭：先膨胀再腐蚀

#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()

# 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()

梯度运算

梯度=膨胀-腐蚀

提取轮廓

#梯度运算
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()

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

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

礼貌与黑帽

礼帽 = 原始输入-开运算结果

提取出刺来

黑帽 = 闭运算-原始输入

只留下一个大致轮廓

#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()

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