opencv python - 去除二值化图像中的小点噪声

Question

我正在做一个文档 reader，将其中的所有文本解析为 google 电子表格，这个脚本应该可以节省我的工作时间，问题是二进制图像有一个很多干扰 pytesseract 的噪音（文本周围的小点）。我怎样才能消除这种噪音？我用来对图像进行二值化的代码是：

import pytesseract
import cv2
import numpy as np
import os
import re
import argparse

#binarization of images
def binarize(img):
    #convert image to grayscale
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    #apply adaptive thresholding
    thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, 2)
    #return thresholded image
    return thresh

#construct argument parser
parser = argparse.ArgumentParser(description='Binarize image and parse text in image to string')
parser.add_argument('-i', '--image', help='path to image', required=True)
parser.add_argument('-o', '--output', help='path to output file', required=True)
args = parser.parse_args()

# load image
img = cv2.imread(args.image)

#binarization of image
thresh = binarize(img)


#show image
cv2.imshow('image', thresh)
cv2.waitKey(0)
cv2.destroyAllWindows()

#save image
cv2.imwrite(args.output+'/imagen3.jpg', thresh)

我要清理的结果图像是：

如果我应用侵蚀，结果如下：

哪个比另一个差

编辑： 原图为：

Answer 1

您只需要增加 Python/OpenCV 中的自适应阈值参数。

输入：

import cv2

# read image
img = cv2.imread("petrol.png")

# convert img to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# do adaptive threshold on gray image
thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 21, 25)

# write results to disk
cv2.imwrite("petrol_threshold.png", thresh)

# display it
cv2.imshow("THRESHOLD", thresh)
cv2.waitKey(0)

结果：

opencv python - 去除二值化图像中的小点噪声

opencv python - remove small points noise in binarized image

python

opencv

image-processing

tesseract

python-tesseract