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
{
	(void)image;
	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, (float)(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
}