org.opencv.core.Core.absdiff()方法的使用及代码示例

x33g5p2x  于2022-01-18 转载在 其他  
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本文整理了Java中org.opencv.core.Core.absdiff()方法的一些代码示例，展示了Core.absdiff()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Core.absdiff()方法的具体详情如下：
包路径：org.opencv.core.Core
类名称：Core
方法名：absdiff

Core.absdiff介绍

[英]Calculates the per-element absolute difference between two arrays or between an array and a scalar.

The function absdiff calculates:

  • Absolute difference between two arrays when they have the same size and type:

dst(I) = saturate(| src1(I) - src2(I)|)

  • Absolute difference between an array and a scalar when the second array is constructed from Scalar or has as many elements as the number of channels in src1:

dst(I) = saturate(| src1(I) - src2|)

  • Absolute difference between a scalar and an array when the first array is constructed from Scalar or has as many elements as the number of channels in src2:

dst(I) = saturate(| src1 - src2(I)|)

where I is a multi-dimensional index of array elements. In case of multi-channel arrays, each channel is processed independently.

Note: Saturation is not applied when the arrays have the depth CV_32S. You may even get a negative value in the case of overflow.
[中]计算两个数组之间或数组与标量之间的每元素绝对差。
函数absdiff计算：
*大小和类型相同的两个数组之间的绝对差异：
dst（I）=饱和（| src1（I）-src2（I）|）
*当第二个数组由Scalar构造或元素数与src1中的通道数相同时，数组与标量之间的绝对差值：
dst（I）=饱和（| src1（I）-src2 |）
*当第一个数组由Scalar构造或元素数与src2中的通道数相同时，标量与数组之间的绝对差值：
dst（I）=饱和（| src1-src2（I）|）
其中I是数组元素的多维索引。对于多通道阵列，每个通道都是独立处理的。
注意：当阵列的深度为CV_32S时，不应用饱和度。在溢出的情况下，您甚至可能会得到负值。

代码示例

代码示例来源：origin: RaiMan/SikuliX2

  1. public static List<Element> detectChanges(Mat base, Mat mChanged) {
  2.  int PIXEL_DIFF_THRESHOLD = 3;
  3.  int IMAGE_DIFF_THRESHOLD = 5;
  4.  Mat mBaseGray = Element.getNewMat();
  5.  Mat mChangedGray = Element.getNewMat();
  6.  Mat mDiffAbs = Element.getNewMat();
  7.  Mat mDiffTresh = Element.getNewMat();
  8.  Mat mChanges = Element.getNewMat();
  9.  List<Element> rectangles = new ArrayList<>();
  10.  Imgproc.cvtColor(base, mBaseGray, toGray);
  11.  Imgproc.cvtColor(mChanged, mChangedGray, toGray);
  12.  Core.absdiff(mBaseGray, mChangedGray, mDiffAbs);
  13.  Imgproc.threshold(mDiffAbs, mDiffTresh, PIXEL_DIFF_THRESHOLD, 0.0, Imgproc.THRESH_TOZERO);
  14.  if (Core.countNonZero(mDiffTresh) > IMAGE_DIFF_THRESHOLD) {
  15.   Imgproc.threshold(mDiffAbs, mDiffAbs, PIXEL_DIFF_THRESHOLD, 255, Imgproc.THRESH_BINARY);
  16.   Imgproc.dilate(mDiffAbs, mDiffAbs, Element.getNewMat());
  17.   Mat se = Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, new Size(5, 5));
  18.   Imgproc.morphologyEx(mDiffAbs, mDiffAbs, Imgproc.MORPH_CLOSE, se);
  19.   List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
  20.   Mat mHierarchy = Element.getNewMat();
  21.   Imgproc.findContours(mDiffAbs, contours, mHierarchy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
  22.   rectangles = contoursToRectangle(contours);
  23.   Core.subtract(mDiffAbs, mDiffAbs, mChanges);
  24.   Imgproc.drawContours(mChanges, contours, -1, new Scalar(255));
  25.   //logShow(mDiffAbs);
  26.  }
  27.  return rectangles;
  28. }

代码示例来源：origin: JavaOpenCVBook/code

  1. public Mat process(Mat inputImage) {
  2.   Mat foregroundImage = new Mat();
  3.   Core.absdiff(backgroundImage,inputImage , foregroundImage);
  4.   return foregroundImage;
  5. }

代码示例来源：origin: openpnp/openpnp

  1. /**
  2.  * Calculate the absolute difference between the previously stored Mat called source1 and the
  3.  * current Mat.
  4.  * 
  5.  * @param source1
  6.  * @param tag
  7.  */
  8. public FluentCv absDiff(String source1, String... tag) {
  9.   Core.absdiff(get(source1), mat, mat);
  10.   return store(mat, tag);
  11. }

代码示例来源：origin: openpnp/openpnp

  1. public static double calculatePsnr(Mat I1, Mat I2) {
  2.   Mat s1 = new Mat();
  3.   Core.absdiff(I1, I2, s1); // |I1 - I2|
  4.   s1.convertTo(s1, CvType.CV_32F); // cannot make a square on 8 bits
  5.   s1 = s1.mul(s1); // |I1 - I2|^2
  6.   Scalar s = Core.sumElems(s1); // sum elements per channel
  7.   double sse = s.val[0] + s.val[1] + s.val[2]; // sum channels
  8.   if (sse <= 1e-10) {
  9.     // for small values return zero
  10.     return 0;
  11.   }
  12.   else {
  13.     double mse = sse / (double) (I1.channels() * I1.total());
  14.     double psnr = 10.0 * Math.log10((255 * 255) / mse);
  15.     return psnr;
  16.   }
  17. }

代码示例来源：origin: openpnp/openpnp

  1. Core.absdiff(lastSettleMat, mat, diff);
  2. MinMaxLocResult result = Core.minMaxLoc(diff);
  3. Logger.debug("autoSettleAndCapture auto settle score: " + result.maxVal);

代码示例来源：origin: JavaOpenCVBook/code

  1. public Mat process(Mat inputImage) {
  2.   Mat foregroundThresh = new Mat();
  3.   // Firstly, convert to gray-level image, yields good results with performance		
  4.   Imgproc.cvtColor(inputImage, inputGray, Imgproc.COLOR_BGR2GRAY);
  5.   // initialize background to 1st frame, convert to floating type
  6.   if (accumulatedBackground.empty())
  7.     inputGray.convertTo(accumulatedBackground, CvType.CV_32F);
  8.   // convert background to 8U, for differencing with input image
  9.   accumulatedBackground.convertTo(backImage,CvType.CV_8U);
  10.   // compute difference between image and background
  11.   Core.absdiff(backImage,inputGray,foreground);
  12.   
  13.   // apply threshold to foreground image
  14.   Imgproc.threshold(foreground,foregroundThresh, threshold,255, Imgproc.THRESH_BINARY_INV);
  15.   
  16.   
  17.   // accumulate background
  18.   Mat inputFloating = new Mat();
  19.   inputGray.convertTo(inputFloating, CvType.CV_32F);
  20.   Imgproc.accumulateWeighted(inputFloating, accumulatedBackground,learningRate, foregroundThresh);
  21.   
  22.   return negative(foregroundThresh);
  23. }

代码示例来源：origin: com.sikulix/sikulixapi

  1. public boolean hasChanges(Mat current) {
  2.  int PIXEL_DIFF_THRESHOLD = 5;
  3.  int IMAGE_DIFF_THRESHOLD = 5;
  4.  Mat bg = new Mat();
  5.  Mat cg = new Mat();
  6.  Mat diff = new Mat();
  7.  Mat tdiff = new Mat();
  8.  Imgproc.cvtColor(base, bg, Imgproc.COLOR_BGR2GRAY);
  9.  Imgproc.cvtColor(current, cg, Imgproc.COLOR_BGR2GRAY);
  10.  Core.absdiff(bg, cg, diff);
  11.  Imgproc.threshold(diff, tdiff, PIXEL_DIFF_THRESHOLD, 0.0, Imgproc.THRESH_TOZERO);
  12.  if (Core.countNonZero(tdiff) <= IMAGE_DIFF_THRESHOLD) {
  13.   return false;
  14.  }
  15.  Imgproc.threshold(diff, diff, PIXEL_DIFF_THRESHOLD, 255, Imgproc.THRESH_BINARY);
  16.  Imgproc.dilate(diff, diff, new Mat());
  17.  Mat se = Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, new Size(5,5));
  18.  Imgproc.morphologyEx(diff, diff, Imgproc.MORPH_CLOSE, se);
  19.  List<MatOfPoint> points = new ArrayList<MatOfPoint>();
  20.  Mat contours = new Mat();
  21.  Imgproc.findContours(diff, points, contours, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
  22.  int n = 0;
  23.  for (Mat pm: points) {
  24.   log(lvl, "(%d) %s", n++, pm);
  25.   printMatI(pm);
  26.  }
  27.  log(lvl, "contours: %s", contours);
  28.  printMatI(contours);
  29.  return true;
  30. }

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