opencv/modules/features2d/src/blobdetector.cpp

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#include "precomp.hpp"
#include <iterator>

//#define DEBUG_BLOB_DETECTOR

#ifdef DEBUG_BLOB_DETECTOR
#include "opencv2/highgui/highgui.hpp"
#endif

using namespace cv;

/*
 *  SimpleBlobDetector
 */
SimpleBlobDetector::Params::Params()
{
  thresholdStep = 10;
  minThreshold = 50;
  maxThreshold = 220;
  minRepeatability = 2;
  minDistBetweenBlobs = 10;

  filterByColor = true;
  blobColor = 0;

  filterByArea = true;
  minArea = 25;
  maxArea = 5000;

  filterByCircularity = false;
  minCircularity = 0.8f;
  maxCircularity = std::numeric_limits<float>::max();

  filterByInertia = true;
  //minInertiaRatio = 0.6;
  minInertiaRatio = 0.1f;
  maxInertiaRatio = std::numeric_limits<float>::max();

  filterByConvexity = true;
  //minConvexity = 0.8;
  minConvexity = 0.95f;
  maxConvexity = std::numeric_limits<float>::max();
}

SimpleBlobDetector::SimpleBlobDetector(const SimpleBlobDetector::Params &parameters) :
  params(parameters)
{
}

void SimpleBlobDetector::findBlobs(const cv::Mat &image, const cv::Mat &binaryImage, vector<Center> &centers) const
{
  centers.clear();

  vector < vector<Point> > contours;
  Mat tmpBinaryImage = binaryImage.clone();
  findContours(tmpBinaryImage, contours, CV_RETR_LIST, CV_CHAIN_APPROX_NONE);

#ifdef DEBUG_BLOB_DETECTOR
//  Mat keypointsImage;
//  cvtColor( binaryImage, keypointsImage, CV_GRAY2RGB );
//
//  Mat contoursImage;
//  cvtColor( binaryImage, contoursImage, CV_GRAY2RGB );
//  drawContours( contoursImage, contours, -1, Scalar(0,255,0) );
//  imshow("contours", contoursImage );
#endif

  for (size_t contourIdx = 0; contourIdx < contours.size(); contourIdx++)
  {
    Center center;
    center.confidence = 1;
    Moments moms = moments(Mat(contours[contourIdx]));
    if (params.filterByArea)
    {
      double area = moms.m00;
      if (area < params.minArea || area >= params.maxArea)
        continue;
    }

    if (params.filterByCircularity)
    {
      double area = moms.m00;
      double perimeter = arcLength(Mat(contours[contourIdx]), true);
      double ratio = 4 * CV_PI * area / (perimeter * perimeter);
      if (ratio < params.minCircularity || ratio >= params.maxCircularity)
        continue;
    }

    if (params.filterByInertia)
    {
      double denominator = sqrt(pow(2 * moms.mu11, 2) + pow(moms.mu20 - moms.mu02, 2));
      const double eps = 1e-2;
      double ratio;
      if (denominator > eps)
      {
        double cosmin = (moms.mu20 - moms.mu02) / denominator;
        double sinmin = 2 * moms.mu11 / denominator;
        double cosmax = -cosmin;
        double sinmax = -sinmin;

        double imin = 0.5 * (moms.mu20 + moms.mu02) - 0.5 * (moms.mu20 - moms.mu02) * cosmin - moms.mu11 * sinmin;
        double imax = 0.5 * (moms.mu20 + moms.mu02) - 0.5 * (moms.mu20 - moms.mu02) * cosmax - moms.mu11 * sinmax;
        ratio = imin / imax;
      }
      else
      {
        ratio = 1;
      }

      if (ratio < params.minInertiaRatio || ratio >= params.maxInertiaRatio)
        continue;

      center.confidence = ratio * ratio;
    }

    if (params.filterByConvexity)
    {
      vector < Point > hull;
      convexHull(Mat(contours[contourIdx]), hull);
      double area = contourArea(Mat(contours[contourIdx]));
      double hullArea = contourArea(Mat(hull));
      double ratio = area / hullArea;
      if (ratio < params.minConvexity || ratio >= params.maxConvexity)
        continue;
    }

    center.location = Point2d(moms.m10 / moms.m00, moms.m01 / moms.m00);

    if (params.filterByColor)
    {
      if (binaryImage.at<uchar> (cvRound(center.location.y), cvRound(center.location.x)) != params.blobColor)
        continue;
    }

    //compute blob radius
    {
      vector<double> dists;
      for (size_t pointIdx = 0; pointIdx < contours[contourIdx].size(); pointIdx++)
      {
        Point2d pt = contours[contourIdx][pointIdx];
        dists.push_back(norm(center.location - pt));
      }
      std::sort(dists.begin(), dists.end());
      center.radius = (dists[(dists.size() - 1) / 2] + dists[dists.size() / 2]) / 2.;
    }

    centers.push_back(center);

#ifdef DEBUG_BLOB_DETECTOR
//    circle( keypointsImage, center.location, 1, Scalar(0,0,255), 1 );
#endif
  }
#ifdef DEBUG_BLOB_DETECTOR
//  imshow("bk", keypointsImage );
//  waitKey();
#endif
}

void SimpleBlobDetector::detectImpl(const cv::Mat& image, std::vector<cv::KeyPoint>& keypoints, const cv::Mat&) const
{
  //TODO: support mask
  keypoints.clear();
  Mat grayscaleImage;
  if (image.channels() == 3)
    cvtColor(image, grayscaleImage, CV_BGR2GRAY);
  else
    grayscaleImage = image;

  vector < vector<Center> > centers;
  for (double thresh = params.minThreshold; thresh < params.maxThreshold; thresh += params.thresholdStep)
  {
    Mat binarizedImage;
    threshold(grayscaleImage, binarizedImage, thresh, 255, THRESH_BINARY);

#ifdef DEBUG_BLOB_DETECTOR
//    Mat keypointsImage;
//    cvtColor( binarizedImage, keypointsImage, CV_GRAY2RGB );
#endif

    vector < Center > curCenters;
    findBlobs(grayscaleImage, binarizedImage, curCenters);
    vector < vector<Center> > newCenters;
    for (size_t i = 0; i < curCenters.size(); i++)
    {
#ifdef DEBUG_BLOB_DETECTOR
//      circle(keypointsImage, curCenters[i].location, curCenters[i].radius, Scalar(0,0,255),-1);
#endif

      bool isNew = true;
      for (size_t j = 0; j < centers.size(); j++)
      {
        double dist = norm(centers[j][ centers[j].size() / 2 ].location - curCenters[i].location);
        isNew = dist >= params.minDistBetweenBlobs && dist >= centers[j][ centers[j].size() / 2 ].radius && dist >= curCenters[i].radius;
        if (!isNew)
        {
          centers[j].push_back(curCenters[i]);

          size_t k = centers[j].size() - 1;
          while( k > 0 && centers[j][k].radius < centers[j][k-1].radius )
          {
            centers[j][k] = centers[j][k-1];
            k--;
          }
          centers[j][k] = curCenters[i];

          break;
        }
      }
      if (isNew)
      {
        newCenters.push_back(vector<Center> (1, curCenters[i]));
        //centers.push_back(vector<Center> (1, curCenters[i]));
      }
    }
    std::copy(newCenters.begin(), newCenters.end(), std::back_inserter(centers));

#ifdef DEBUG_BLOB_DETECTOR
//    imshow("binarized", keypointsImage );
    //waitKey();
#endif
  }

  for (size_t i = 0; i < centers.size(); i++)
  {
    if (centers[i].size() < params.minRepeatability)
      continue;
    Point2d sumPoint(0, 0);
    double normalizer = 0;
    for (size_t j = 0; j < centers[i].size(); j++)
    {
      sumPoint += centers[i][j].confidence * centers[i][j].location;
      normalizer += centers[i][j].confidence;
    }
    sumPoint *= (1. / normalizer);
    KeyPoint kpt(sumPoint, centers[i][centers[i].size() / 2].radius);
    keypoints.push_back(kpt);
  }

#ifdef DEBUG_BLOB_DETECTOR
  namedWindow("keypoints", CV_WINDOW_NORMAL);
  Mat outImg = image.clone();
  for(size_t i=0; i<keypoints.size(); i++)
  {
    circle(outImg, keypoints[i].pt, keypoints[i].size, Scalar(255, 0, 255), -1);
  }
  //drawKeypoints(image, keypoints, outImg);
  imshow("keypoints", outImg);
  waitKey();
#endif
}