How to read the Data Matrix Code with OpenCV python

Question

I amd trying to read a datamatrix code on the metal surface. The datamatrix code was engraved with laser welding. I tried pylibdmtx with image preprocessing.

Data Matrix Code engraved with Laser on Metal Surface

Here is my code and the result. Unfortunately, I could not read the data from the preprocessed image.

enter image description here

import cv2
import numpy as np

'''
1. Image Read
2. Image Process
  a. gray scale
  b. crop image
  c. EqualizeHist
  d. Thres Binaray 152
  e. Blur
  f. Threshod otsu
  g. bitwise not
   
3. Result image save
'''

# crop image
def crop_image(image, min_x, max_x, min_y, max_y):
    # Load the image

    # Get image dimensions
    height, width = image.shape[:2]
    print(height, width)

    # Calculate the crop sizes
    crop_left = int(min_x * width)
    crop_right = int((1 - max_x) * width)
    crop_top = int(min_y * height)
    crop_bottom = int((1 - max_y) * height)

    print(crop_left, crop_right)

    # Crop the image
    cropped_image = image[crop_top:crop_bottom, crop_left:crop_right]
    print(cropped_image.shape)

    # Return the cropped image
    return cropped_image


# cv2 createTrackbar
def empty(x):
    pass


cv2.namedWindow('Parameters')
cv2.resizeWindow('Parameters', width=600, height=400)
cv2.createTrackbar('min_x', 'Parameters', 38, 100, empty)  # crop x
cv2.createTrackbar('max_x', 'Parameters', 36, 100, empty)  # crop x
cv2.createTrackbar('min_y', 'Parameters', 43, 100, empty)  # crop x
cv2.createTrackbar('max_y', 'Parameters', 10, 100, empty)  # crop x
cv2.createTrackbar('threshold', 'Parameters', 136, 255, empty)  # threshold
cv2.createTrackbar('k_size_set', 'Parameters', 18, 20, empty)  # blur
cv2.createTrackbar('k_mat_set', 'Parameters', 2, 5, empty) #k_mat
cv2.createTrackbar('iter_d', 'Parameters', 2, 30, empty)  # 5
cv2.createTrackbar('iter_e', 'Parameters', 4, 30, empty)  # 5

img = cv2.imread('./image/live.png')
# Gray Scale
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# resize
img = cv2.resize(img, dsize=None, fx=0.5, fy=0.5)

# -----------------------------------------------
#
# -----------------------------------------------

while True:
    ## 00. Make a Copy
    img_copy = img.copy()
    img_black = np.zeros_like(img)

    # 1. Crop Image
    dx_min = cv2.getTrackbarPos('min_x', 'Parameters')
    dx_max = cv2.getTrackbarPos('max_x', 'Parameters')
    dy_min = cv2.getTrackbarPos('min_y', 'Parameters')
    dy_max = cv2.getTrackbarPos('max_y', 'Parameters')

    dx_min, dx_max = dx_min / 100, dx_max / 100
    dy_min, dy_max = dy_min / 100, dy_max / 100

    img_crop = crop_image(image=img_copy, min_x=dx_min, max_x=dx_max, min_y=dy_min, max_y=dy_max)

    # 3 Equalize hist
    img_hist = cv2.equalizeHist(img_crop)

    # 4. Thres Binaray 152
    thres = cv2.getTrackbarPos('threshold', 'Parameters')
    _, img_thresh = cv2.threshold(img_hist, thres, 255, cv2.THRESH_BINARY)

    # 5. Gaussian Blur
    kernel = cv2.getTrackbarPos('k_size_set', 'Parameters')
    kernel = (kernel * 2) + 1
    img_blur = cv2.GaussianBlur(img_thresh, (kernel, kernel), None)

    # 6. Threshod otsu
    _, img_thresh2 = cv2.threshold(img_blur, 0, 255, cv2.THRESH_OTSU)

    # 7kernel : dilate , erodeのkernelの定義に注意
    kernel2 = cv2.getTrackbarPos('k_mat_set', 'Parameters')
    kernel2 = (kernel2 * 2) + 1
    k_mat = np.ones((kernel2, kernel2), np.uint8)

    # 8. Dilate
    iter_dilate = cv2.getTrackbarPos('iter_d', 'Parameters')
    img_dilate = cv2.dilate(img_thresh2, kernel=k_mat, iterations=iter_dilate)

    # 9. Erode
    iter_erode = cv2.getTrackbarPos('iter_e', 'Parameters')
    img_erode = cv2.erode(img_dilate, kernel=k_mat, iterations=iter_erode)

    # Plotting
  
    cv2.imshow('result2' ,img_erode)

   
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cv2.imwrite('./image/result2.png', img_erode)
print('saved')
cv2.destroyAllWindows()

Here is my image preprocessing procedures:

1. Image Read

2. Image Process a. gray scale b. crop image c. EqualizeHist d. Thres Binaray e. Blur f. Threshod otsu g. bitwise not

3. Result image save