To segment the image using global thresholding, adaptive thresholding and Otsu's thresholding using python and OpenCV.
- Anaconda - Python 3.7
- OpenCV
Load the necessary packages.
Read the Image and convert to grayscale.
Use Global thresholding to segment the image.
Use Adaptive thresholding to segment the image.
Use Otsu's method to segment the image and display the results.
#Name: M.Shyam Naveen Raj
#Reg No: 212221230099
# Load the necessary packages
import numpy as np
import matplotlib.pyplot as plt
import cv2
# Read the Image and convert to grayscale
image = cv2.imread('cheetah.jpeg',1)
image = cv2.cvtColor(image,cv2.COLOR_BGR2RGB)
image_gray = cv2.imread('cheetah.jpeg',0)
# Use Global thresholding to segment the image
ret,thresh_img1=cv2.threshold(image_gray,86,255,cv2.THRESH_BINARY)
ret,thresh_img2=cv2.threshold(image_gray,86,255,cv2.THRESH_BINARY_INV)
ret,thresh_img3=cv2.threshold(image_gray,86,255,cv2.THRESH_TOZERO)
ret,thresh_img4=cv2.threshold(image_gray,86,255,cv2.THRESH_TOZERO_INV)
ret,thresh_img5=cv2.threshold(image_gray,100,255,cv2.THRESH_TRUNC)
# Use Adaptive thresholding to segment the image
thresh_img7=cv2.adaptiveThreshold(image_gray,255,cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,11,2)
thresh_img8=cv2.adaptiveThreshold(image_gray,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,11,2)
# Use Otsu's method to segment the image
ret,thresh_img6=cv2.threshold(image_gray,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)
# Display the results
titles=["Gray Image","Threshold Image (Binary)","Threshold Image (Binary Inverse)","Threshold Image (To Zero)"
,"Threshold Image (To Zero-Inverse)","Threshold Image (Truncate)","Otsu","Adaptive Threshold (Mean)","Adaptive Threshold (Gaussian)"]
images=[image_gray,thresh_img1,thresh_img2,thresh_img3,thresh_img4,thresh_img5,thresh_img6,thresh_img7,thresh_img8]
for i in range(0,9):
plt.figure(figsize=(10,10))
plt.subplot(1,2,1)
plt.title("Original Image")
plt.imshow(image)
plt.axis("off")
plt.subplot(1,2,2)
plt.title(titles[i])
plt.imshow(cv2.cvtColor(images[i],cv2.COLOR_BGR2RGB))
plt.axis("off")
plt.show()
Thus the images are segmented using global thresholding, adaptive thresholding and optimum global thresholding using python and OpenCV.