OpenCV从入门到精通——形态学操作

膨胀

-求局部最大值
- 对目标像素点进行扩展
import cv2

img = cv2.imread("./images/4.jpg",cv2.IMREAD_GRAYSCALE)

kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(3,3))

dst = cv2.dilate(img,kernel)
cv2.imshow("src",img)
cv2.imshow("dst",dst)
cv2.waitKey(0)

腐蚀

• 局部最小值
• 对目标像素点进行缩减

import cv2

img = cv2.imread("./images/4.jpg",cv2.IMREAD_GRAYSCALE)

kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(3,3))
# 膨胀
# dst = cv2.dilate(img,kernel)
dst = cv2.erode(img,kernel)

cv2.imshow("src",img)
cv2.imshow("dst",dst)
cv2.waitKey(0)

开操作

• 先腐蚀后膨胀
• 以用来消除小物体，在纤细点处分离物体，并且在平滑较大物体的边界的同时不明显改变其面积（去除噪声及平滑目标边界）

import cv2

img = cv2.imread("./images/4.jpg",cv2.IMREAD_GRAYSCALE)

kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(3,3))
# 膨胀
# dst = cv2.dilate(img,kernel)
# dst = cv2.erode(img,kernel)

dst = cv2.morphologyEx(img,cv2.MORPH_OPEN,kernel)
cv2.imshow("src",img)
cv2.imshow("dst",dst)
cv2.waitKey(0)

闭操作

• 先膨胀再腐蚀
• 消除小型黑洞

import cv2

img = cv2.imread("./images/4.jpg",cv2.IMREAD_GRAYSCALE)

kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(3,3))
# 膨胀
# dst = cv2.dilate(img,kernel)
# dst = cv2.erode(img,kernel)
dst = cv2.morphologyEx(img,cv2.MORPH_CLOSE,kernel)

# dst = cv2.morphologyEx(img,cv2.MORPH_OPEN,kernel)
cv2.imshow("src",img)
cv2.imshow("dst",dst)
cv2.waitKey(0)

• 结果图

顶帽操作

• 原图像（减数）与“开运算”（被减数）的结果图之差。
• 拿到目标区域的噪音
• 
  

import cv2

img = cv2.imread("./images/4.jpg",cv2.IMREAD_GRAYSCALE)

kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(3,3))
# 膨胀
# dst = cv2.dilate(img,kernel)
# dst = cv2.erode(img,kernel)
# dst = cv2.morphologyEx(img,cv2.MORPH_CLOSE,kernel)
# dst = cv2.morphologyEx(img,cv2.MORPH_OPEN,kernel)
# 顶帽
dst = cv2.morphologyEx(img,cv2.MORPH_TOPHAT,kernel)

cv2.imshow("src",img)
cv2.imshow("dst",dst)
cv2.waitKey(0)

黑帽操作

• 闭-原图拿到目标区域的洞
• 
  

import cv2

img = cv2.imread("./images/4.jpg",cv2.IMREAD_GRAYSCALE)

kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(3,3))
# 膨胀
# dst = cv2.dilate(img,kernel)
# dst = cv2.erode(img,kernel)
# dst = cv2.morphologyEx(img,cv2.MORPH_CLOSE,kernel)
# dst = cv2.morphologyEx(img,cv2.MORPH_OPEN,kernel)
# 顶帽
# dst = cv2.morphologyEx(img,cv2.MORPH_TOPHAT,kernel)
dst = cv2.morphologyEx(img,cv2.MORPH_BLACKHAT,kernel)

cv2.imshow("src",img)
cv2.imshow("dst",dst)
cv2.waitKey(0)

梯度

• 获取梯度

import cv2

img = cv2.imread("./images/4.jpg",cv2.IMREAD_GRAYSCALE)

kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(3,3))
# 膨胀
# dst = cv2.dilate(img,kernel)
# dst = cv2.erode(img,kernel)
# dst = cv2.morphologyEx(img,cv2.MORPH_CLOSE,kernel)
# dst = cv2.morphologyEx(img,cv2.MORPH_OPEN,kernel)
# 顶帽
# dst = cv2.morphologyEx(img,cv2.MORPH_TOPHAT,kernel)
# dst = cv2.morphologyEx(img,cv2.MORPH_BLACKHAT,kernel)
dst = cv2.morphologyEx(img,cv2.MORPH_GRADIENT,kernel)


cv2.imshow("src",img)
cv2.imshow("dst",dst)
cv2.waitKey(0)