Python OpenCV 形态学操作（腐蚀膨胀，开运算和闭运算）

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Python OpenCV 形态学操作（腐蚀膨胀，开运算和闭运算）


过滤器生成

kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))  # 椭圆结构
kernel = cv2.getStructuringElement(cv2.MORPH_CROSS, (3, 3))  # 十字结构
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))  # 矩形结构

腐蚀膨胀开、闭运算

# -*-encoding:utf-8-*-
import pytesseract
from PIL import Image
from PIL import ImageFilter
from PIL import ImageFont
from PIL import ImageDraw
import numpy as np
from PIL import Image

import cv2


def main():
    # img = cv2.imread("test001.jpg") #读取图片
    # cv2.imshow("1",img) #显示图片
    # cv2.waitKey(10000)# 延时10s

    # image = Image.open("test002.png")
    # img = image.convert('1')  # 转化为灰度图

    # img.show()

    img = cv2.imread("test002.png", 0)
    kernel = np.ones((3, 3), np.uint8)  # 全为1的过滤数组
    print(kernel)

    # 腐蚀(去白小点)
    img2 = cv2.erode(img, kernel)  # 腐蚀
    cv2.imshow('canny', img2)
    cv2.waitKey(2000)
    # cv2.waitKey()

    # 膨胀(去黑小点)
    img3 = cv2.dilate(img, kernel)  # 膨胀
    cv2.imshow('canny', img3)
    cv2.waitKey(2000)
    # cv2.waitKey()

    # 先腐蚀后膨胀叫开运算（因为先腐蚀会分开物体，这样容易记住），其作用是：分离物体，消除小区域。
    opening = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel)  # 开运算
    cv2.imshow('canny', opening)
    cv2.waitKey(2000)

    # 闭运算则相反：先膨胀后腐蚀（先膨胀会使白色的部分扩张，以至于消除/"闭合"物体里面的小黑洞，所以叫闭运算）
    closing = cv2.morphologyEx(img, cv2.MORPH_CLOSE, kernel)  # 闭运算
    cv2.imshow('canny', closing)
    cv2.waitKey(2000)


if __name__ == '__main__':
    main()

形态学梯度

# -*-encoding:utf-8-*-
import pytesseract
from PIL import Image
from PIL import ImageFilter
from PIL import ImageFont
from PIL import ImageDraw
import numpy as np
from PIL import Image

import cv2

def main():
    # img = cv2.imread("test001.jpg") #读取图片
    # cv2.imshow("1",img) #显示图片
    # cv2.waitKey(10000)# 延时10s

    # image = Image.open("test002.png")
    # img = image.convert('1')  # 转化为灰度图

    # img.show()

    img = cv2.imread("test002.png", 0)
    kernel = np.ones((3, 3), np.uint8)  # 全为1的过滤数组
    print(kernel)

    # 形态学梯度：膨胀图减去腐蚀图，dilation - erosion，这样会得到物体的轮廓：
    gradient = cv2.morphologyEx(img, cv2.MORPH_GRADIENT, kernel)  # 形态学梯度
    cv2.imshow('canny', gradient)
    cv2.waitKey(2000)


if __name__ == '__main__':
    main()

顶帽黑帽

# -*-encoding:utf-8-*-
import pytesseract
from PIL import Image
from PIL import ImageFilter
from PIL import ImageFont
from PIL import ImageDraw
import numpy as np
from PIL import Image

import cv2


def main():
    # img = cv2.imread("test001.jpg") #读取图片
    # cv2.imshow("1",img) #显示图片
    # cv2.waitKey(10000)# 延时10s

    # image = Image.open("test002.png")
    # img = image.convert('1')  # 转化为灰度图

    # img.show()

    img = cv2.imread("test002.png", 0)
    kernel = np.ones((3, 3), np.uint8)  # 全为1的过滤数组
    print(kernel)

    # 顶帽：原图减去开运算后的图
    tophat = cv2.morphologyEx(img, cv2.MORPH_TOPHAT, kernel)
    cv2.imshow('canny', tophat)
    cv2.waitKey(2000)

    # 黑帽：闭运算后的图减去原图
    blackhat = cv2.morphologyEx(img, cv2.MORPH_BLACKHAT, kernel)
    cv2.imshow('canny', blackhat)
    cv2.waitKey(2000)


if __name__ == '__main__':
    main()