使用 python 图像处理识别材料上的 ID

Question

我想阅读线圈上的文字（一些由数字组成的 ID）。但是 OCR 程序无法识别它。当我给出小部分时，它只能识别线性部分（3个数字）。我认为这是因为 ID 是半圆形的。我必须检测 ID，并且我正在使用带有 tesseract 库的 python 代码。我怎样才能做到这一点？谢谢。

Photo for image processing

# import the necessary packages
import numpy as np
import pytesseract
import argparse
import imutils
import cv2


pytesseract.pytesseract.tesseract_cmd = 'C:\\Program Files\\Tesseract-OCR\\tesseract.exe'
image = cv2.imread('1.jpg')

#Cropping and having Region Of Interest
(h, w) = image.shape[:2]
ROI = image[200:450, 1100:1550]
cv2.imshow("ROI", ROI)

gray = cv2.cvtColor(ROI, cv2.COLOR_BGR2GRAY)
cv2.imshow("ROI", gray)

# threshold the image using Otsu's thresholding method
thresh = cv2.threshold(gray, 0, 255,
        cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
cv2.imshow("Otsu", thresh)

options = "--psm 3 -c tessedit_char_whitelist=0123456789"
text = pytesseract.image_to_string(thresh, config=options)
print(text)

cv2.waitKey(0)

Answer 1

1. Detect the ID in the image.
2. Crop the ID from the image.
3. Resize the cropped image to a fixed size.
4. Apply OCR to the resized image.

检查这个： https://github.com/souravs17031999/ID-Extractor-from-Coil

import cv2
import numpy as np
import pytesseract
from PIL import Image

# Path of working folder on Disk

def get_string(img_path):
    # Read image with opencv
    img = cv2.imread(img_path)

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

    # Apply dilation and erosion to remove some noise
    kernel = np.ones((1, 1), np.uint8)
    img = cv2.dilate(img, kernel, iterations=1)
    img = cv2.erode(img, kernel, iterations=1)

    # Write image after removed noise
    cv2.imwrite("removed_noise.png", img)

    #  Apply threshold to get image with only black and white
    #img = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2)

    # Write the image after apply opencv to do some ...
    cv2.imwrite(img_path, img)

    # Recognize text with tesseract for python
    result = pytesseract.image_to_string(Image.open(img_path))

    # Remove template file
    

    return result