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Measure similarity between images using Python-OpenCV
  • Last Updated : 10 Jul, 2020

Prerequisites: Python OpenCV

Suppose we have two data images and a test image. Let’s find out which data image is more similar to the test image using python and OpenCV library in Python.

Let’s first load the image and find out the histogram of images.

Importing library

import cv2

Importing image data



image = cv2.imread('test.jpg')

Converting to gray image

gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

Finding Histogram

histogram = cv2.calcHist([gray_image], [0], 
                              None, [256], [0, 256])

Example:

Images used:

data1.jpg

data2.jpg

test.jpg

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code

import cv2
   
      
# test image
image = cv2.imread('cat.jpg')
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
histogram = cv2.calcHist([gray_image], [0], 
                         None, [256], [0, 256])
   
# data1 image
image = cv2.imread('cat.jpeg')
gray_image1 = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
histogram1 = cv2.calcHist([gray_image1], [0], 
                          None, [256], [0, 256])
   
# data2 image
image = cv2.imread('food.jpeg')
gray_image2 = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
histogram2 = cv2.calcHist([gray_image2], [0], 
                          None, [256], [0, 256])
   
   
c1, c2 = 0, 0
   
# Euclidean Distace between data1 and test
i = 0
while i<len(histogram) and i<len(histogram1):
    c1+=(histogram[i]-histogram1[i])**2
    i+= 1
c1 = c1**(1 / 2)
   
  
# Euclidean Distace between data2 and test
i = 0
while i<len(histogram) and i<len(histogram2):
    c2+=(histogram[i]-histogram2[i])**2
    i+= 1
c2 = c2**(1 / 2)
   
if(c1<c2):
    print("data1.jpg is more similar to test.jpg as compare to data2.jpg")
else:
    print("data2.jpg is more similar to test.jpg as compare to data1.jpg")

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Output :

data1.jpg is more similar to test.jpg as compare to data2.jpg

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