I\'m trying to read a datamatrix barcodes on the bottom of microtubes. I tried libdmtx which has python bindings and works reasonably well when the dots of the matrix are square
It turns out that the Harris corner detector (B) finds the round elements very well with proper settings.
After thresholding (C) we detect contours of the resulting areas. We select the largest contour (D) and find a minimal bounding box (E).
import matplotlib.pyplot as plt
import numpy as np
import cv2
well = plt.imread('https://i.stack.imgur.com/kqHkw.png')
well = cv2.cvtColor(well, cv2.COLOR_BGRA2GRAY)
plt.subplot(151); plt.title('A')
plt.imshow(well)
harris = cv2.cornerHarris(well,4, 1,0.00)
plt.subplot(152); plt.title('B')
plt.imshow(harris)
x, thr = cv2.threshold(harris, 0.1 * harris.max(), 255, cv2.THRESH_BINARY)
thr = thr.astype('uint8')
plt.subplot(153); plt.title('C')
plt.imshow(thr)
dst, contours, hierarchy = cv2.findContours(thr.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
areas = map(lambda x: cv2.contourArea(cv2.convexHull(x)), contours)
max_i = areas.index(max(areas))
d = cv2.drawContours(np.zeros_like(thr), contours, max_i, 255, 1)
plt.subplot(154); plt.title('D')
plt.imshow(d)
rect =cv2.minAreaRect(contours[max_i])
box = cv2.boxPoints(rect)
box = np.int0(box)
e= cv2.drawContours(well,[box],0,1,1)
plt.subplot(155); plt.title('E')
plt.imshow(e)
plt.show()