将相机拍摄的图像与计算机生成的图像进

Question

我正在制作一个应用程序，将相机拍摄的图像与计算机生成的图像进行比较，这些图像存储在数据库中。 我正在使用Opencv进行图像比较，但它只是正确地比较了计算机生成的图像。当我用相机捕获相同的图像并将该图像与计算机生成的图像进行比较时，它与它们不能完全匹配。是否有任何方式可以比较相机图像;

这是我的代码

 public static void main(String[] args) {
  // Set image path
  String path = System.getProperty("user.dir");
  String filename1 = path+"/images/266.jpg";
  String filename2 = path+"/images/20160805_121529.jpg";

  int ret;
  ret = compareFeature(filename1, filename2);

  if (ret > 0) {
   System.out.println("Two images are same.");
  } else {
   System.out.println("Two images are different.");
  }
 }

 /**
  * Compare that two images is similar using feature mapping  
  * @author minikim
  * @param filename1 - the first image
  * @param filename2 - the second image
  * @return integer - count that has the similarity within images 
  */
 public static int compareFeature(String filename1, String filename2) {
  int retVal = 0;
  long startTime = System.currentTimeMillis();

  System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

  // Load images to compare
  Mat img1 = Imgcodecs.imread(filename1, Imgcodecs.CV_LOAD_IMAGE_COLOR);
  Mat img2 = Imgcodecs.imread(filename2, Imgcodecs.CV_LOAD_IMAGE_COLOR);

  // Declare key point of images
  MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
  MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
  Mat descriptors1 = new Mat();
  Mat descriptors2 = new Mat();

  // Definition of ORB key point detector and descriptor extractors
  FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB); 
  DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.ORB);

  // Detect key points
  detector.detect(img1, keypoints1);
  detector.detect(img2, keypoints2);

  // Extract descriptors
  extractor.compute(img1, keypoints1, descriptors1);
  extractor.compute(img2, keypoints2, descriptors2);

  // Definition of descriptor matcher
  DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);

  // Match points of two images
  MatOfDMatch matches = new MatOfDMatch();
//  System.out.println("Type of Image1= " + descriptors1.type() + ", Type of Image2= " + descriptors2.type());
//  System.out.println("Cols of Image1= " + descriptors1.cols() + ", Cols of Image2= " + descriptors2.cols());

  // Avoid to assertion failed
  // Assertion failed (type == src2.type() && src1.cols == src2.cols && (type == CV_32F || type == CV_8U)
  if (descriptors2.cols() == descriptors1.cols()) {
   matcher.match(descriptors1, descriptors2 ,matches);

   // Check matches of key points
   DMatch[] match = matches.toArray();
   double max_dist = 0; double min_dist = 100;

   for (int i = 0; i < descriptors1.rows(); i++) { 
    double dist = match[i].distance;
       if( dist < min_dist ) min_dist = dist;
       if( dist > max_dist ) max_dist = dist;
   }
   System.out.println("max_dist=" + max_dist + ", min_dist=" + min_dist);

      // Extract good images (distances are under 10)
   for (int i = 0; i < descriptors1.rows(); i++) {
    if (match[i].distance <= 10) {
     retVal++;
    }
   }
   System.out.println("matching count=" + retVal);
  }

  long estimatedTime = System.currentTimeMillis() - startTime;
  System.out.println("estimatedTime=" + estimatedTime + "ms");

  return retVal;
 }

这是我正在比较的图片

这是相机拍摄的图像

先谢谢