java中的图像比较[关闭]答案

【问题标题】：image comparison in java [closed]java中的图像比较[关闭]
【发布时间】：2011-09-03 09:10:10
【问题描述】：

我正在做我的大学项目，在该项目中我需要进行指纹比较。这可以通过比较两个图像并匹配它们的像素相似性来完成（根据我的发现）。

是否有任何 API/库/SDK 或 Java 中可用的任何东西，用于比较两个图像并获得它们之间的百分比匹配？

【问题讨论】：

我不知道任何API，但是您只是想比较每个像素的像素颜色并获得平均差异吗？
使用像素比较两张图片并获取它们之间的相似度

标签： java api image-processing sdk

【解决方案1】：

查看OpenCV 库。你可以在那里找到你需要的东西。以here 为例，了解如何比较图像。

【讨论】：

【解决方案2】：

这样的东西对你有用吗？注释行可能不太正确。

int numberOfPixels = 0;
float runningTotal = 0;    
for (int i = 0; i < image.width; i++)
{
    for (int j = 0; j < image.height; j++)
    {
        //Color a = image1.getPixel(i, j);
        //Color b = image2.getPixel(i, j);

        float differenceRed = abs(a.red() - b.red()) / 255;
        float differenceGreen = abs(a.green() - b.green()) / 255;
        float differenceBlue = abs(a.blue() - b.blue()) / 255;

        float differenceForThisPixel = (differenceRed + differenceGreen + differenceBlue) / 3;
        runningTotal += differenceForThisPixel;
        numberOfPixels++;

    }
}
averageDifference = (runningTotal / numberOfPixels);

【讨论】：

在某些情况下使用此方法可以完成工作，但是在大多数情况下还不够。图像相似度不是通过像素到像素的比较来衡量的；它应该涉及图案比较、阴影比较、对比度比较等。我希望生活就这么简单:-)

【解决方案3】：

图像相似度

比较两个BufferedImage 像素与pixel 并显示相似度。图片尺寸（宽度/高度）必须相同。

 public static double similarity( BufferedImage image1, BufferedImage image2 ) throws IOException{
         int total_no_ofPixels = 0;      
         int image1_PixelColor, red, blue, green;
         int image2_PixelColor, red2, blue2, green2;
         float differenceRed, differenceGreen, differenceBlue, differenceForThisPixel;
         double nonSimilarPixels = 0l, non_Similarity = 0l;

         long startTime = System.nanoTime();
// A digital image is a rectangular grid of pixels, Dimensions with/Height = 1366/728 pixels.        
// Colours are usually expressed in terms of a combination of red, green and blue values.        
         for (int row = 0; row < image1.getWidth(); row++) {
            for (int column = 0; column < image1.getHeight(); column++) {
                  image1_PixelColor   =  image1.getRGB(row, column);                
                  red                 = (image1_PixelColor & 0x00ff0000) >> 16;
                  green               = (image1_PixelColor & 0x0000ff00) >> 8;
                  blue                =  image1_PixelColor & 0x000000ff;

                  image2_PixelColor   =  image2.getRGB(row, column);                
                  red2                = (image2_PixelColor & 0x00ff0000) >> 16;
                  green2              = (image2_PixelColor & 0x0000ff00) >> 8;
                  blue2               =  image2_PixelColor & 0x000000ff;

                        if (red != red2 || green != green2 || blue != blue2) {
                            differenceRed   =  red - red2 / 255;
                            differenceGreen = ( green - green2 ) / 255;
                            differenceBlue  = ( blue - blue2 ) / 255;
                            differenceForThisPixel = ( differenceRed + differenceGreen + differenceBlue ) / 3;
                            nonSimilarPixels += differenceForThisPixel;
                        }
                 total_no_ofPixels++;

                 if ( image1_PixelColor != image2_PixelColor ) {
                     image2.setRGB(row, column, Color.green.getGreen());
                 }
            }
        }
         long endTime = System.nanoTime();
         System.out.println(String.format( "%-2d: %s", 0, toString( endTime - startTime )));

         System.out.println(" Writing the difference of first_Image to Second_Image ");
         ImageIO.write(image2, "jpeg", new File("D:\\image2.png"));

         non_Similarity = (nonSimilarPixels / total_no_ofPixels);
         System.out.println( "Total No of pixels : " + total_no_ofPixels +"\t Non Similarity is : " + non_Similarity +"%");

         return non_Similarity;          
     }
     private static String toString(long nanoSecs) {
          int minutes    = (int) ( nanoSecs / 60000000000.0 );
          int seconds    = (int) ( nanoSecs / 1000000000.0 )  - ( minutes * 60 );
          int millisecs  = (int) ( (( nanoSecs / 1000000000.0 ) - ( seconds + minutes * 60 )) * 1000 );

          if      ( minutes == 0 && seconds == 0   )    return millisecs + "ms";
          else if ( minutes == 0 && millisecs == 0 )    return seconds + "s";
          else if ( seconds == 0 && millisecs == 0 )    return minutes + "min";
          else if ( minutes == 0                   )    return seconds + "s " + millisecs + "ms";
          else if ( seconds == 0                   )    return minutes + "min " + millisecs + "ms";
          else if ( millisecs == 0                 )    return minutes + "min " + seconds + "s";

          return minutes + "min " + seconds + "s " + millisecs + "ms";
       }

James Webster 帖子的简要说明

【讨论】：

小改进：差异写成“jpeg”不太好找像素写成绿色，用“png”更好。