膨胀 : 相当于最大值滤波,用矩阵中最大值替换中心元素,扩大白色区域
腐蚀:相当于最小值滤波。最小值替换中心像素,扩大黑色区域
操作类似
先转灰度,在二值化,最后腐蚀或膨胀
# 核的大小和形状
kernel = cv.getStructuringElement(cv.MORPH_RECT, (5, 5))
# 执行四次腐蚀操作
erode = cv.erode(binary, kernel, iterations=4)
# 膨胀操作
erode = cv.dilate(binary, kernel, iterations=4)
import cv2 as cv
import numpy as np
img = cv.imread("tooth.png")
cv.imshow('img', img)
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow('gray', gray)
ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY | cv.THRESH_OTSU)
cv.imshow('bin', binary)
# 核的大小和形状
kernel = cv.getStructuringElement(cv.MORPH_RECT, (5, 5))
# 执行四次腐蚀操作
erode = cv.erode(binary, kernel, iterations=4)
# 膨胀操作
# erode = cv.dilate(binary, kernel, iterations=4)
cv.imshow('erode', erode)
cv.waitKey(0)
转载至链接:/ahaoboy/blog/1922050