使用均值漂移算法查找物体，源代码

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#if !defined OFINDER
#define OFINDER#include <opencv2\core\core.hpp>
#include <opencv2\imgproc\imgproc.hpp>class ContentFinder {private:float hranges[2];const float* ranges[3];int channels[3];float threshold;cv::MatND histogram;cv::SparseMat shistogram;bool isSparse;public:ContentFinder() : threshold(0.1f), isSparse(false) {ranges[0]= hranges; // all channels have the same range ranges[1]= hranges; ranges[2]= hranges; }// Sets the threshold on histogram values [0,1]void setThreshold(float t) {threshold= t;}// Gets the thresholdfloat getThreshold() {return threshold;}// Sets the reference histogramvoid setHistogram(const cv::MatND& h) {isSparse= false;histogram= h;cv::normalize(histogram,histogram,1.0);}// Sets the reference histogramvoid setHistogram(const cv::SparseMat& h) {isSparse= true;shistogram= h;cv::normalize(shistogram,shistogram,1.0,cv::NORM_L2);}cv::Mat find(const cv::Mat& image) {cv::Mat result;hranges[0]= 0.0;	// range [0,255]hranges[1]= 255.0;channels[0]= 0;		// the three channels channels[1]= 1; channels[2]= 2; if (isSparse) { // call the right function based on histogram typecv::calcBackProject(&image,1,            // one imagechannels,     // vector specifying what histogram dimensions belong to what image channelsshistogram,   // the histogram we are usingresult,       // the resulting back projection imageranges,       // the range of values, for each dimension255.0         // the scaling factor is chosen such that a histogram value of 1 maps to 255);} else {cv::calcBackProject(&image,1,            // one imagechannels,     // vector specifying what histogram dimensions belong to what image channelshistogram,    // the histogram we are usingresult,       // the resulting back projection imageranges,       // the range of values, for each dimension255.0         // the scaling factor is chosen such that a histogram value of 1 maps to 255);}// Threshold back projection to obtain a binary imageif (threshold>0.0)cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY);return result;}cv::Mat find(const cv::Mat& image, float minValue, float maxValue, int *channels, int dim) {cv::Mat result;hranges[0]= minValue;hranges[1]= maxValue;for (int i=0; i<dim; i++)this->channels[i]= channels[i];if (isSparse) { // call the right function based on histogram typecv::calcBackProject(&image,1,            // we only use one image at a timechannels,     // vector specifying what histogram dimensions belong to what image channelsshistogram,   // the histogram we are usingresult,       // the resulting back projection imageranges,       // the range of values, for each dimension255.0         // the scaling factor is chosen such that a histogram value of 1 maps to 255);} else {cv::calcBackProject(&image,1,            // we only use one image at a timechannels,     // vector specifying what histogram dimensions belong to what image channelshistogram,    // the histogram we are usingresult,       // the resulting back projection imageranges,       // the range of values, for each dimension255.0         // the scaling factor is chosen such that a histogram value of 1 maps to 255);}// Threshold back projection to obtain a binary imageif (threshold>0.0)cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY);return result;}};#endif#if !defined COLHISTOGRAM
#define COLHISTOGRAM#include <opencv2\core\core.hpp>
#include <opencv2\imgproc\imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>
class ColorHistogram {private:int histSize[3];float hranges[2];const float* ranges[3];int channels[3];public:ColorHistogram() {// Prepare arguments for a color histogramhistSize[0]= histSize[1]= histSize[2]= 256;hranges[0]= 0.0;    // BRG rangehranges[1]= 255.0;ranges[0]= hranges; // all channels have the same range ranges[1]= hranges; ranges[2]= hranges; channels[0]= 0;		// the three channels channels[1]= 1; channels[2]= 2; }// Computes the histogram.cv::MatND getHistogram(const cv::Mat &image) {cv::MatND hist;// BGR color histogramhranges[0]= 0.0;    // BRG rangehranges[1]= 255.0;channels[0]= 0;		// the three channels channels[1]= 1; channels[2]= 2; // Compute histogramcv::calcHist(&image, 1,			// histogram of 1 image onlychannels,	// the channel usedcv::Mat(),	// no mask is usedhist,		// the resulting histogram3,			// it is a 3D histogramhistSize,	// number of binsranges		// pixel value range);return hist;}// Computes the 1D Hue histogram with a mask.// BGR source image is converted to HSVcv::MatND getHueHistogram(const cv::Mat &image) {cv::MatND hist;// Convert to Lab color spacecv::Mat hue;cv::cvtColor(image, hue, CV_BGR2HSV);// Prepare arguments for a 1D hue histogramhranges[0]= 0.0;hranges[1]= 180.0;channels[0]= 0; // the hue channel // Compute histogramcv::calcHist(&hue, 1,			// histogram of 1 image onlychannels,	// the channel usedcv::Mat(),	// no mask is usedhist,		// the resulting histogram1,			// it is a 1D histogramhistSize,	// number of binsranges		// pixel value range);return hist;}cv::MatND getHueHistogram(const cv::Mat &image,int minSaturation){cv::MatND hist;cv::Mat hsv;cv::cvtColor(image,hsv,CV_BGR2HSV);cv::Mat mask;if(minSaturation>0){std::vector<cv::Mat>v;cv::split(hsv,v);cv::threshold(v[1],mask,minSaturation,255,cv::THRESH_BINARY);}hranges[0]=0.0;hranges[1]=180.0;channels[0]=0;calcHist(&hsv,1,channels,mask,hist,1,histSize,ranges);return hist;}};#endif#include<opencv2/core/core.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/video/video.hpp>
#include<iostream>
#include"colorhistogram.h"
#include"ContentFinder.h"using namespace std;
using namespace cv;int main()
{Mat image=imread("d:/test/opencv/baboon1.jpg");Mat imageROI=image(Rect(110,260,35,40));int minSat=65;ColorHistogram hc;MatND colorhist=hc.getHueHistogram(imageROI,minSat);namedWindow("image 1");imshow("image 1",image);ContentFinder finder;finder.setHistogram(colorhist);Mat hsv;image=imread("d:/test/opencv/baboon3.jpg");namedWindow("image 2");imshow("image 2",image);cvtColor(image,hsv,CV_BGR2HSV);vector<Mat>v;split(hsv,v);threshold(v[1],v[1],minSat,255,THRESH_BINARY);cv::namedWindow("Saturation");cv::imshow("Saturation",v[1]);int channel[1]={0};Mat result=finder.find(hsv,0.0f,180.0f,channel,1);cv::namedWindow("Result Hue");cv::imshow("Result Hue",result);cv::bitwise_and(result,v[1],result);cv::namedWindow("Result Hue and");cv::imshow("Result Hue and",result);finder.setThreshold(-1.0f);//result= finder.find(hsv,0.0f,180.0f,channel,1);cv::bitwise_and(result,v[1],result);cv::namedWindow("Result Hue and raw");cv::imshow("Result Hue and raw",result);cv::Rect rect(110,260,35,40);cv::rectangle(image, rect, cv::Scalar(0,0,255));cv::TermCriteria criteria(cv::TermCriteria::MAX_ITER,10,0.01);cout << "meanshift= " << cv::meanShift(result,rect,criteria) << endl;//cv::rectangle(image, rect, cv::Scalar(0,255,0));//// Display imagecv::namedWindow("Image 2 result");cv::imshow("Image 2 result",image);cv::waitKey();return 0;}

 

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