一：顶帽实现（原图像与开操作图像的差值）
import cv2
as cv
import numpy as np
def top_hat_demo(image):
gray =
cv.cvtColor(image,cv.COLOR_BGR2GRAY)
ret,binary = cv.threshold(gray,
0,
255,cv.THRESH_BINARY|
cv.THRESH_OTSU)
cv.imshow("binary",binary) #这里的二值化图像就可以看作是原图像（注意：基于腐蚀膨胀是可以直接对彩色图像操作的））
kernel = cv.getStructuringElement(cv.MORPH_ELLIPSE,(
5,
5))
dst =
cv.morphologyEx(binary,cv.MORPH_OPEN,kernel) #查看开操作图像
cv.imshow("open_demo",dst)
dst =
cv.morphologyEx(binary,cv.MORPH_TOPHAT,kernel) #查看顶帽图像
cv.imshow("top_hat_demo",dst)
src = cv.imread(
"./cir.png") #读取图片
cv.namedWindow("input image",cv.WINDOW_AUTOSIZE) #创建GUI窗口,形式为自适应
cv.imshow("input image",src) #通过名字将图像和窗口联系
top_hat_demo(src)
cv.waitKey(0) #等待用户操作，里面等待参数是毫秒，我们填写0，代表是永远，等待用户操作
cv.destroyAllWindows() #销毁所有窗口
二：黑帽实现（原图像与闭操作图像的差值）
def black_hat_demo(image):
gray =
cv.cvtColor(image,cv.COLOR_BGR2GRAY)
ret,binary = cv.threshold(gray,
0,
255,cv.THRESH_BINARY|
cv.THRESH_OTSU)
cv.imshow("binary",binary)
kernel = cv.getStructuringElement(cv.MORPH_RECT,(
15,
15))
dst =
cv.morphologyEx(binary,cv.MORPH_CLOSE,kernel)
cv.imshow("close_demo",dst)
dst =
cv.morphologyEx(binary,cv.MORPH_BLACKHAT,kernel)
cv.imshow("black_hat_demo",dst)
三：图像的梯度
（一）基本梯度（膨胀后的图像与腐蚀后的图像差值）
def graditent_demo(image):
gray =
cv.cvtColor(image,cv.COLOR_BGR2GRAY)
ret,binary = cv.threshold(gray,
0,
255,cv.THRESH_BINARY|
cv.THRESH_OTSU)
cv.imshow("binary",binary)
kernel = cv.getStructuringElement(cv.MORPH_RECT,(
15,
15))
dst =
cv.dilate(binary, kernel)
cv.imshow("dilate_demo", dst)
dst =
cv.erode(binary, kernel)
cv.imshow("erode_demo", dst)
dst =
cv.morphologyEx(binary,cv.MORPH_GRADIENT,kernel)
cv.imshow("graditent_demo",dst)
（二）内部梯度（原图像减去腐蚀后的图像差值）
def graditent_demo(image):
gray =
cv.cvtColor(image,cv.COLOR_BGR2GRAY)
ret,binary = cv.threshold(gray,
0,
255,cv.THRESH_BINARY|
cv.THRESH_OTSU)
cv.imshow("binary",binary)
kernel = cv.getStructuringElement(cv.MORPH_RECT,(
15,
15))
erode_dst =
cv.erode(binary, kernel)
cv.imshow("erode_demo", erode_dst)
dst2 =
cv.subtract(dilate_dst,binary)
cv.imshow("inner graditent",dst1)
（三）外部梯度（膨胀后图像与原图差值）
def graditent_demo(image):
gray =
cv.cvtColor(image,cv.COLOR_BGR2GRAY)
ret,binary = cv.threshold(gray,
0,
255,cv.THRESH_BINARY|
cv.THRESH_OTSU)
cv.imshow("binary",binary)
kernel = cv.getStructuringElement(cv.MORPH_RECT,(
15,
15))
dilate_dst =
cv.dilate(binary, kernel)
cv.imshow("dilate_demo", dilate_dst)
dst2 =
cv.subtract(dilate_dst,binary)
cv.imshow("outer graditent",dst2)
转载于:https://www.cnblogs.com/ssyfj/p/9277891.html
相关资源：opencv-3.2.0.zip
