OpenCV 形態學轉換

綜述

OpenCV中的形態學轉換操作有七種：腐蝕，膨脹，開運算，閉運算，形態學梯度，禮帽，黑帽。

API參照表

中文名	英文名	api	原理	個人理解
腐蝕	erode	erosion = cv2.erode(src=girl_pic, kernel=kernel)	在窗中，只要含有０，則窗內全變爲０，可以去淺色噪點	淺色成分被腐蝕
膨脹	dilate	dilation = cv2.dilate(src=girl_pic, kernel=kernel)	在窗中，只要含有１，則窗內全變爲１，可以增加淺色成分	淺色成分得膨脹
開運算	morphology-open	opening = cv2.morphologyEx(girl_pic, cv2.MORPH_OPEN, kernel)	先腐蝕，後膨脹，去白噪點	先合再開，對淺色成分不利
閉運算	morphology-close	closing = cv2.morphologyEx(girl_pic, cv2.MORPH_CLOSE, kernel)	先膨脹，後腐蝕，去黑噪點	先開再合，淺色成分得勢
形態學梯度	morphology-grandient	gradient = cv2.morphologyEx(girl_pic, cv2.MORPH_GRADIENT, kernel)	一幅圖像腐蝕與膨脹的區別，可以得到輪廓	數值上解釋爲：膨脹減去腐蝕
禮帽	tophat	tophat = cv2.morphologyEx(girl_pic, cv2.MORPH_TOPHAT, kernel)	原圖像減去開運算的差	數值上解釋爲：原圖像減去開運算
黑帽	blackhat	blackhat = cv2.morphologyEx(girl_pic, cv2.MORPH_BLACKHAT, kernel)	閉運算減去原圖像的差	數值上解釋爲：閉運算減去原圖像

# -*- coding: utf-8 -*-

import cv2
import numpy as np

girl_pic = cv2.imread('timg.jpg')

kernel = np.ones((5, 5), np.uint8)

# erode 腐蝕
erosion = cv2.erode(src=girl_pic, kernel=kernel)
cv2.imshow('erosion', erosion)
cv2.imwrite('pic/erosion.jpg', erosion)

# dilate　膨脹
dilation = cv2.dilate(src=girl_pic, kernel=kernel)
cv2.imshow('dilation', dilation)
cv2.imwrite('pic/dilation.jpg', dilation)

# open　開運算
opening = cv2.morphologyEx(girl_pic, cv2.MORPH_OPEN, kernel)
cv2.imshow('opening', opening)
cv2.imwrite('pic/opening.jpg', opening)

# close　閉運算
closing = cv2.morphologyEx(girl_pic, cv2.MORPH_CLOSE, kernel)
cv2.imshow('closing', closing)
cv2.imwrite('pic/closing.jpg', closing)

# gradient　形態學梯度
gradient = cv2.morphologyEx(girl_pic, cv2.MORPH_GRADIENT, kernel)
cv2.imshow('gradient', gradient)
cv2.imwrite('pic/gradient.jpg', gradient)

# tophat　禮帽
tophat = cv2.morphologyEx(girl_pic, cv2.MORPH_TOPHAT, kernel)
cv2.imshow('tophat', tophat)
cv2.imwrite('pic/tophat.jpg', tophat)

# blackhat　黑帽
blackhat = cv2.morphologyEx(girl_pic, cv2.MORPH_BLACKHAT, kernel)
cv2.imshow('blackhat', blackhat)
cv2.imwrite('pic/blackhat.jpg', blackhat)

# cv2.add(open, tophat)　cv2.add(開運算, 禮帽)
open_and_tophat = cv2.add(opening, tophat)
cv2.imshow('open_and_tophat', open_and_tophat)
cv2.imwrite('pic/open_and_tophat.jpg', open_and_tophat)

# close-blackhat　閉運算-黑帽
close_subtract_blackhat = closing - blackhat
cv2.imshow('close_subtract_blackhat', close_subtract_blackhat)
cv2.imwrite('pic/close_subtract_blackhat.jpg', close_subtract_blackhat)
k = cv2.waitKey(0)

if k == 27:  # 按下ESC退出
    cv2.destroyAllWindows()

https://blog.csdn.net/jningwei/article/details/76101668