opencv基於混合高斯模型的圖像分割

#include "stdafx.h"
#include <opencv\cv.h>
#include <opencv\highgui.h>
#include <opencv2\legacy\legacy.hpp>

int _tmain(int argc, _TCHAR* argv[])
{
    CvEM em_model;
    //CvEM em_model2;
    CvEMParams params;
    int N=3;
    //設置模型參數
    params.covs      = NULL;
    params.means     = NULL;
    params.weights   = NULL;
    params.probs     = NULL;
    params.nclusters = N;
    params.cov_mat_type       = CvEM::COV_MAT_SPHERICAL;
    //params.cov_mat_type       = CvEM::COV_MAT_DIAGONAL;
    params.start_step         = CvEM::START_AUTO_STEP;
    params.term_crit.max_iter = 10;
    params.term_crit.epsilon  = 0.1;
    params.term_crit.type     = CV_TERMCRIT_ITER|CV_TERMCRIT_EPS;

    IplImage* img=cvLoadImage("frame18843.jpg");//加載圖像，圖像放在Debug文件夾裏，這裏是相對路徑

    cvNamedWindow( "原始圖像", 1 ); //建立窗口
    cvShowImage( "原始圖像", img  ); //顯示圖像
    //cvWaitKey(0); //等待按鍵


    int i,j;
    CvMat *samples=cvCreateMat((img->width)*(img->height),3,CV_32FC1);//建立樣本矩陣，CV_32FC3表明32位浮點3通道（彩色圖像）
    CvMat *clusters=cvCreateMat((img->width)*(img->height),1,CV_32SC1);//建立類別標記矩陣，CV_32SF1表明32位整型1通道
    cvReshape( samples, samples, 3, 0 );
    int k=0;
    for (i=0;i<img->width;i++)
    {
        for (j=0;j<img->height;j++)
        {
            CvScalar s;
            //獲取圖像各個像素點的三通道值（RGB）
            s.val[0]=(float)cvGet2D(img,j,i).val[0];
            s.val[1]=(float)cvGet2D(img,j,i).val[1];
            s.val[2]=(float)cvGet2D(img,j,i).val[2];
            cvSet2D(samples,k++,0,s);//將像素點三通道的值按順序排入樣本矩陣
        }
    }
    int nCuster=3;//聚類類別數，本身修改。
    //cvKMeans2(samples,nCuster,clusters,cvTermCriteria(CV_TERMCRIT_ITER,100,1.0));//開始聚類，迭代100次，終止偏差1.0
    cvReshape( samples, samples, 1, 0 );
    em_model.train( samples, 0, params, clusters );

    IplImage *bin=cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_8U,1);//建立用於顯示的圖像，二值圖像
    k=0;
    int val=0;
    float step=255/(nCuster-1);
    for (i=0;i<img->width;i++)
    {
        for (j=0;j<img->height;j++)
        {
            val=(int)clusters->data.i[k++];
            CvScalar s;
            s.val[0]=255-val*step;//這個是將不一樣類別取不一樣的像素值，
            cvSet2D(bin,j,i,s); //將每一個像素點賦值 
        }
    }
    cvNamedWindow( "聚類圖像", 1 ); //建立窗口
    cvShowImage( "聚類圖像", bin  ); //顯示圖像
    cvWaitKey(0); //等待按鍵
    cvDestroyWindow( "原始圖像" );//銷燬窗口
    cvReleaseImage( &img ); //釋放圖像
    cvDestroyWindow( "聚類圖像" );//銷燬窗口
    cvReleaseImage( &bin ); //釋放圖像
    return 0;
}