THRESHOLDING

Aim

To segment the image using global thresholding, adaptive thresholding and Otsu's thresholding using python and OpenCV.

Software Required

Anaconda - Python 3.7
OpenCV

Algorithm

Step1:

Import Required package.

Step2:

Read input image and convert into gray scale.Display the image.

Step3:

Use global threshold to segment the image.Display the image.

Step4:

Use adaptive threshold to segment the image.Display the image.

Step5:

Use Otsu's threshold to segment the image.Display the image.

Program

# Load the necessary packages

import cv2



# Read the Image and convert to grayscale

img = cv2.imread('test_image.png',1)
cv2.imshow('original_image',img)
cv2.waitKey(0)
cv2.destroyAllWindows
gray =cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
cv2.imshow('gray_image',gray)
cv2.waitKey(0)
cv2.destroyAllWindows


# Use Global thresholding to segment the image

ret,thresh_img1=cv2.threshold(gray,86,255,cv2.THRESH_BINARY)
ret,thresh_img2=cv2.threshold(gray,86,255,cv2.THRESH_BINARY_INV)
ret,thresh_img3=cv2.threshold(gray,100,255,cv2.THRESH_TRUNC)
ret,thresh_img4=cv2.threshold(gray,86,255,cv2.THRESH_TOZERO)
ret,thresh_img5=cv2.threshold(gray,86,255,cv2.THRESH_TOZERO_INV)


cv2.imshow('Threshold Binary',thresh_img1)
cv2.imshow('Threshold Binary Inverse',thresh_img2)
cv2.imshow('Threshold Trunc',thresh_img3)
cv2.imshow('Threshold To Zero',thresh_img4)
cv2.imshow('Threshold To Zero Inverse',thresh_img5)

cv2.waitKey(0)
cv2.destroyAllWindows


# Use Adaptive thresholding to segment the image

thresh_img6=cv2.adaptiveThreshold(gray,255,cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,11,2)
thresh_img7=cv2.adaptiveThreshold(gray,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,11,2)

cv2.imshow('Adaptive Threshold Mean',thresh_img6)
cv2.imshow('Adaptive Thresh Gaussian',thresh_img7)

cv2.waitKey(0)
cv2.destroyAllWindows


# Use Otsu's method to segment the image 

ret,thresh_img8=cv2.threshold(gray,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)

cv2.imshow('Otsu Method',thresh_img8)

cv2.waitKey(0)
cv2.destroyAllWindows