I made a simple image similarity calculator using JAVA.

I made a simple image similarity calculator using JAVA.
Key Algorithms: Copy code 1 // full process 2 public static void main (String [] args) throws IOException {3 // get image 4 File imageFile = new File ("c: /1.jpg"); 5 Image image = ImageIO. read (imageFile); 6 // convert to grayscale 7 image = toGrayscale (image); 8 // scale down to a thumbnail of 32x32 9 image = scale (image ); 10 // obtain the gray pixel array 11 int [] pixels = getPixels (image); 12 // obtain the average gray color 13 int averageColor = getAverageOfPixelArray (pixels ); 14 // obtain the comparison array of gray pixels (that is, the image fingerprint sequence) 15 Pixels = getPixelDeviateWeightsArray (pixels, averageColor, pixels); 18 // calculate the similarity using the Hamming distance. value range: [0.0, 1.0] 19 double similarity = calSimilarity (hammingDistance ); 20} 21 22 // convert any Image type to BufferedImage type to facilitate subsequent operations 23 public static BufferedImage convertToBufferedFrom (Image srcImage) {24 BufferedImage bufferedImage = n Ew BufferedImage (srcImage. getWidth (null), 25 srcImage. getHeight (null), BufferedImage. TYPE_INT_ARGB); 26 Graphics2D g = bufferedImage. createGraphics (); 27g. drawImage (srcImage, null, null); 28g. dispose (); 29 return bufferedImage; 30} 31 32 // convert to grayscale fig 33 public static BufferedImage toGrayscale (Image image) {34 BufferedImage sourceBuffered = convertToBufferedFrom (image ); 35 ColorSpace cs = ColorSpace. getInst Ance (ColorSpace. CS_GRAY); 36 ColorConvertOp op = new ColorConvertOp (cs, null); 37 BufferedImage grayBuffered = op. filter (sourceBuffered, null); 38 return grayBuffered; 39} 40 41 // zoom to 32x32 pixel thumbnail 42 public static Image scale (Image image) {43 image = image. getScaledInstance (32, 32, Image. SCALE_SMOOTH); 44 return image; 45} 46 47 // get the pixel array 48 public static int [] getPixels (Image image) {49 int width = image. g EtWidth (null); 50 int height = image. getHeight (null); 51 int [] pixels = convertToBufferedFrom (image ). getRGB (0, 0, width, height, 52 null, 0, width); 53 return pixels; 54} 55 56 // obtain the average pixel Color value of the grayscale image 57 public static int getAverageOfPixelArray (int [] pixels) {58 color; 59 long sumRed = 0; 60 for (int I = 0; I <pixels. length; I ++) {61 color = new Color (pixels [I], true); 62 sumRed + = color. getRed (); 63} 64 in T averageRed = (int) (sumRed/pixels. length); 65 return averageRed; 66} 67 68 // retrieve the pixel comparison array of the grayscale image (mean deviation) 69 public static int [] getPixelDeviateWeightsArray (int [] pixels, final int averageColor) {70 Color color; 71 int [] dest = new int [pixels. length]; 72 for (int I = 0; I <pixels. length; I ++) {73 color = new Color (pixels [I], true); 74 dest [I] = color. getRed ()-averageColor> 0? 1: 0; 75} 76 return dest; 77} 78 79 // obtain the Hamming distance of the array from the average pixels of the two thumbnails (the larger the distance, the larger the difference) 80 public static int getHammingDistance (int [] a, int [] B) {81 int sum = 0; 82 for (int I = 0; I <. length; I ++) {83 sum + = a [I] = B [I]? 0: 1; 84} 85 return sum; 86} 87 88 // calculate similarity 89 public static double calSimilarity (int hammingDistance) {90 int length = 32*32 using the hammingDistance distance; 91 double similarity = (length-hammingDistance)/(double) length; 92 93 // use an exponential curve to adjust the similarity result 94 similarity = java. lang. math. pow (similarity, 2); 95 return similarity; 96} copy code