ThresholdingAdaptive.py

import cv2
from matplotlib import pyplot as plt

def ShowImgWithMatplotlib(colorImg, title, pos):
    imgRGB = colorImg[:, :, ::-1]
    ax = plt.subplot(2, 3, pos)
    plt.imshow(imgRGB)
    plt.title(title)
    plt.axis('off')

fig = plt.figure(figsize=(15, 7))
plt.suptitle("Adaptive thresholding", fontsize=14, fontweight='bold')
fig.patch.set_facecolor('silver')

image = cv2.imread('images/sudoku.png')
grayImage = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
thresh1 = cv2.adaptiveThreshold(grayImage, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 11, 2)
thresh2 = cv2.adaptiveThreshold(grayImage, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 31, 3)
thresh3 = cv2.adaptiveThreshold(grayImage, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)
thresh4 = cv2.adaptiveThreshold(grayImage, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 3)

ShowImgWithMatplotlib(cv2.cvtColor(grayImage, cv2.COLOR_GRAY2BGR), "gray img", 1)
ShowImgWithMatplotlib(cv2.cvtColor(thresh1, cv2.COLOR_GRAY2BGR), "method=THRESH_MEAN_C, blockSize=11, C=2", 2)
ShowImgWithMatplotlib(cv2.cvtColor(thresh2, cv2.COLOR_GRAY2BGR), "method=THRESH_MEAN_C, blockSize=31, C=3", 3)
ShowImgWithMatplotlib(cv2.cvtColor(thresh3, cv2.COLOR_GRAY2BGR), "method=GAUSSIAN_C, blockSize=11, C=2", 5)
ShowImgWithMatplotlib(cv2.cvtColor(thresh4, cv2.COLOR_GRAY2BGR), "method=GAUSSIAN_C, blockSize=31, C=3", 6)

plt.show()