代码如下:
#导入cv模块
import cv2 as cv
import numpy as np
#开操作,删除小的干扰快
def open_demo(image):
print(image.shape)
gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
# ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY | cv.THRESH_OTSU)
ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY_INV | cv.THRESH_OTSU)
cv.imshow("binary image", binary)
# kernel=cv.getStructuringElement(cv.MORPH_RECT,(15,1))#提取水平线
# kernel = cv.getStructuringElement(cv.MORPH_RECT, (1, 15)) # 提取竖着的线
kernel = cv.getStructuringElement(cv.MORPH_RECT, (4, 4)) # 提取竖着的线
binary=cv.morphologyEx(binary,cv.MORPH_OPEN,kernel)
cv.imshow("open-result",binary)
#闭操作
def close_demo(image):
print(image.shape)
gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY | cv.THRESH_OTSU)
cv.imshow("binary image", binary)
kernel=cv.getStructuringElement(cv.MORPH_RECT,(15,

本文介绍了OpenCV中的开闭操作在图像处理中的应用,通过代码示例展示了如何实现这一功能,并提供了参考链接以深入学习形态学的其他操作。
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