OpenCV 3 Computer Vision with Python Cookbook

How to do it...

Perform the following steps:

1. Import the packages:

import cv2import numpy as npimport matplotlib.pyplot as plt

2. Read the test image:

image = cv2.imread('../data/Lena.png', 0)

3. Apply a simple binary threshold:

thr, mask = cv2.threshold(image, 200, 1, cv2.THRESH_BINARY)print('Threshold used:', thr)

4. Apply adaptive thresholding:

adapt_mask = cv2.adaptiveThreshold(image, 255, cv2.ADAPTIVE_THRESH_MEAN_C,                                   cv2.THRESH_BINARY_INV, 11, 10)

5. Visualize the results:

plt.figure(figsize=(10,3))plt.subplot(131)plt.axis('off')plt.title('original')plt.imshow(image, cmap='gray')plt.subplot(132)plt.axis('off')plt.title('binary threshold')plt.imshow(mask, cmap='gray')plt.subplot(133)plt.axis('off')plt.title('adaptive threshold')plt.imshow(adapt_mask, ...