Image Processing in Java | Set 14 ( Comparison of two images )

We strongly recommend to refer below posts as a prerequisite of this.

In this article we will learn how to compare two given images (must be of same dimensions) and print the percentage of difference between them.

Algorithm:

Step 1 – Check if dimensions of both the image match.
Step 2 – Get the RGB values of both images.
Step 3 – Calculate the difference in two corresponding pixel of three color components.
Step 4 – Repeat Step 2-3 for each pixel of the images.
Step 5 – Calculate the percentage by dividing the sum of differences with:

Number of pixels, to obtain the average difference per pixel
3, to obtain the average difference per color component
255, to obtain a value between 0.0 and 1.0 which can be converted into a percent value

Implementation:

// Java Program to compare two images 
import java.awt.image.BufferedImage; 
import javax.imageio.ImageIO; 
import java.io.File; 
import java.io.IOException; 
  
class ImageComparision 
{ 
    public static void main(String[] args) 
    { 
        BufferedImage imgA = null; 
        BufferedImage imgB = null; 
  
        try
        { 
            File fileA = new File("/home / pratik /"+ 
                             " Desktop / image1.jpg"); 
            File fileB = new File("/home / pratik /"+ 
                             " Desktop / image2.jpg"); 
  
            imgA = ImageIO.read(fileA); 
            imgB = ImageIO.read(fileB); 
        } 
        catch (IOException e) 
        { 
            System.out.println(e); 
        } 
        int width1 = imgA.getWidth(); 
        int width2 = imgB.getWidth(); 
        int height1 = imgA.getHeight(); 
        int height2 = imgB.getHeight(); 
  
        if ((width1 != width2) || (height1 != height2)) 
            System.out.println("Error: Images dimensions"+ 
                                             " mismatch"); 
        else
        { 
            long difference = 0; 
            for (int y = 0; y < height1; y++) 
            { 
                for (int x = 0; x < width1; x++) 
                { 
                    int rgbA = imgA.getRGB(x, y); 
                    int rgbB = imgB.getRGB(x, y); 
                    int redA = (rgbA >> 16) & 0xff; 
                    int greenA = (rgbA >> 8) & 0xff; 
                    int blueA = (rgbA) & 0xff; 
                    int redB = (rgbB >> 16) & 0xff; 
                    int greenB = (rgbB >> 8) & 0xff; 
                    int blueB = (rgbB) & 0xff; 
                    difference += Math.abs(redA - redB); 
                    difference += Math.abs(greenA - greenB); 
                    difference += Math.abs(blueA - blueB); 
                } 
            } 
  
            // Total number of red pixels = width * height 
            // Total number of blue pixels = width * height 
            // Total number of green pixels = width * height 
            // So total number of pixels = width * height * 3 
            double total_pixels = width1 * height1 * 3; 
  
            // Normalizing the value of different pixels 
            // for accuracy(average pixels per color 
            // component) 
            double avg_different_pixels = difference / 
                                          total_pixels; 
  
            // There are 255 values of pixels in total 
            double percentage = (avg_different_pixels / 
                                            255) * 100; 
  
            System.out.println("Difference Percentage-->" + 
                                                percentage); 
        } 
    } 
} 

NOTE:Code will not run on online ide since it requires image in drive.

Output:

Input images:

Output : Difference Percentage–>2.843600130405922

Input images:

Output : Difference Percentage–>6.471412648669786

Input images:

Output : Difference Percentage–>0.0

This article is contributed by Pratik Agarwal. If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

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