JAVA做了个简易图像相似度计算器

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使用最简单最基础的感知哈希算法，算法原理戳这里，绝对比笔主讲的要好：

http://www.ruanyifeng.com/blog/2011/07/principle_of_similar_image_search.html
UI设计图：
实际运行效果图：
关键算法：
 1 // 全流程 2 public static void main(String[] args) throws IOException { 3     // 获取图像 4     File imageFile = new File("c:/1.jpg"); 5     Image image = ImageIO.read(imageFile); 6     // 转换至灰度 7     image = toGrayscale(image); 8     // 缩小成32x32的缩略图 9     image = scale(image);10     // 获取灰度像素数组11     int[] pixels = getPixels(image);12     // 获取平均灰度颜色13     int averageColor = getAverageOfPixelArray(pixels);14     // 获取灰度像素的比较数组（即图像指纹序列）15     pixels = getPixelDeviateWeightsArray(pixels, averageColor);16     // 获取两个图的汉明距离（假设另一个图也已经按上面步骤得到灰度比较数组）17     int hammingDistance = getHammingDistance(pixels, pixels);18     // 通过汉明距离计算相似度，取值范围 [0.0, 1.0]19     double similarity = calSimilarity(hammingDistance);20 }21 22 // 将任意Image类型图像转换为BufferedImage类型，方便后续操作23 public static BufferedImage convertToBufferedFrom(Image srcImage) {24     BufferedImage bufferedImage = new BufferedImage(srcImage.getWidth(null),25             srcImage.getHeight(null), BufferedImage.TYPE_INT_ARGB);26     Graphics2D g = bufferedImage.createGraphics();27     g.drawImage(srcImage, null, null);28     g.dispose();29     return bufferedImage;30 }31 32 // 转换至灰度图33 public static BufferedImage toGrayscale(Image image) {34     BufferedImage sourceBuffered = convertToBufferedFrom(image);35     ColorSpace cs = ColorSpace.getInstance(ColorSpace.CS_GRAY);36     ColorConvertOp op = new ColorConvertOp(cs, null);37     BufferedImage grayBuffered = op.filter(sourceBuffered, null);38     return grayBuffered;39 }40 41 // 缩放至32x32像素缩略图42 public static Image scale(Image image) {43     image = image.getScaledInstance(32, 32, Image.SCALE_SMOOTH);44     return image;45 }46 47 // 获取像素数组48 public static int[] getPixels(Image image) {49     int width = image.getWidth(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 // 获取灰度图的平均像素颜色值57 public static int getAverageOfPixelArray(int[] pixels) {58     Color 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     int averageRed = (int) (sumRed / pixels.length);65     return averageRed;66 }67 68 // 获取灰度图的像素比较数组（平均值的离差）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 // 获取两个缩略图的平均像素比较数组的汉明距离（距离越大差异越大）80 public static int getHammingDistance(int[] a, int[] b) {81     int sum = 0;82     for (int i = 0; i < a.length; i++) {83         sum += a[i] == b[i] ? 0 : 1;84     }85     return sum;86 }87 88 // 通过汉明距离计算相似度89 public static double calSimilarity(int hammingDistance){90     int length = 32*32;91     double similarity = (length - hammingDistance) / (double) length;92 93     // 使用指数曲线调整相似度结果94     similarity = java.lang.Math.pow(similarity, 2);95     return similarity;96 }
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