如何用OpenCV在去除收据阴影后清理背景并保留字符信息

我已用Python代码实现收据图像的阴影去除，但因膨胀（dilation）和中值模糊（medianBlur）操作，字符周围仍存在噪声。尝试过阈值化处理，却会丢失部分字符信息。现寻求能清理背景同时保留字符完整性与清晰度的算法，以实现有效的文本提取。

现有阴影去除代码 #

import cv2
import pytesseract
import sys
import numpy as np


sys.stdout.reconfigure(encoding='utf-8')
pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'

imRGB = cv2.imread(r'D:\Senior-project\images\028.jpg')


split_color_channels = cv2.split(imRGB)
print(split_color_channels)

color_channels_result = []
color_norm_channels_result = []

for color_channel in split_color_channels:

    img_dilation = cv2.dilate(color_channel, np.ones((7,7), np.uint8))

    blur_img = cv2.medianBlur(img_dilation, 21)

    diff_img = 255 - cv2.absdiff(color_channel, blur_img)

    norm_img = cv2.normalize(diff_img,None, alpha=0, beta=255, norm_type=cv2.NORM_MINMAX)
    
    color_channels_result.append(diff_img)
    color_norm_channels_result.append(norm_img)
result = cv2.merge(color_channels_result)
result_norm = cv2.merge(color_norm_channels_result)
print(result_norm.shape)


cv2.imwrite(r'image.jpg', result_norm)

image = cv2.imread(r'D:\1204314 - Computer Vision and Image Processing\Week1\Lab0101\image.jpg')
print(image.shape)

图像对比 #

原始图像 #

阴影去除后图像 #

内容的提问来源于stack exchange，提问作者Theeraphat Khlangphukhiao