Chapter 7

1. ret, thresh = cv2.threshold(gray_image, 100, 255, cv2.THRESH_BINARY)
2. thresh = cv2.adaptiveThreshold(gray_image, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 9, 2)
3. ret, th = cv2.threshold(gray_image, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
4. ret, th = cv2.threshold(gray_image, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_TRIANGLE)
5. Otsu's thresholding using scikit-image can be applied as follows:

thresh = threshold_otsu(gray_image)
binary = gray_image > thresh
binary = img_as_ubyte(binary)

Remember that the threshold_otsu(gray_image) function returns the threshold value based on Otsu's binarization algorithm. Afterwards, with this value, the binary image is constructed (dtype= bool), which should be converted into an 8-bit unsigned integer format (dtype= uint8) for proper visualization. The img_as_ubyte() function is used for this purpose.

6. Triangle...