使用opencv python从二进制图像中移除小白点

Question

我有一个二进制图像，我想用opencv从图像中删除小白点Python。你这里可以参考我的问题enter link description here

我最初的形象是

我希望输出图像为：

Answer 1

你可以使用“关闭”功能-腐蚀后扩张。它不需要模糊功能。在

import cv2 as cv
import numpy as np

img = cv.imread('original',0)
kernel = np.ones((5,5),np.uint8)

opening = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel)

cv2.imshow('original', img)
cv2.imshow('output', opening)
cv2.waitKey(0)
cv2.destroyAllWindows()

Answer 2

您可以简单地使用图像平滑技术（如高斯模糊等）来去除图像中的噪声，然后进行如下二值化阈值处理：

img = cv2.imread("your-image.png",0)
blur = cv2.GaussianBlur(img,(13,13),0)
thresh = cv2.threshold(blur, 100, 255, cv2.THRESH_BINARY)[1]

cv2.imshow('original', img)
cv2.imshow('output', thresh)
cv2.waitKey(0)
cv2.destroyAllWinsdows()

输出：

阅读here中的不同图像平滑/模糊技术。在

Answer 3

使用Python Opencv中的连接组件似乎可以做到这一点。在

#!/bin/python3.7

import cv2
import numpy as np

src = cv2.imread('img.png', cv2.IMREAD_GRAYSCALE)

# convert to binary by thresholding
ret, binary_map = cv2.threshold(src,127,255,0)

# do connected components processing
nlabels, labels, stats, centroids = cv2.connectedComponentsWithStats(binary_map, None, None, None, 8, cv2.CV_32S)

#get CC_STAT_AREA component as stats[label, COLUMN] 
areas = stats[1:,cv2.CC_STAT_AREA]

result = np.zeros((labels.shape), np.uint8)

for i in range(0, nlabels - 1):
    if areas[i] >= 100:   #keep
        result[labels == i + 1] = 255

cv2.imshow("Binary", binary_map)
cv2.imshow("Result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()

cv2.imwrite("Filterd_result.png, result)

见here