multigaussian.cpp

不错的beijingfenge的程序

// MeanShift.cpp : Defines the entry point for the console application.
//

#include "stdafx.h"

#ifdef _CH_
#pragma package <opencv>
#endif

#ifndef _EiC
#include "cv.h"
#include "highgui.h"
#include <stdio.h>
#include <ctype.h>
#include "cvaux.h"
#endif


//////////////////////////////////////////////////////////////////////////

CvSeq* m_contour = NULL;
CvRect m_contour_rect = cvRect(0,0,0,0); 
CvMemStorage* m_storage = cvCreateMemStorage(0);


int main( int argc, char** argv )
{
    CvCapture* m_capture = 0;
    
	m_capture = cvCaptureFromAVI( "C:\\video7_long.avi" );
           			      
	//建立多高斯背景模型
	
	IplImage* tmp_frame = 0;
	IplImage* dst = 0;
			
	if(!m_capture)
	{
		//MessageBox("读取视频文件失败，请重新打开真彩色(24位)视频!", "错误信息", MB_OK );
	    //return;
	}
			
	tmp_frame = cvQueryFrame(m_capture);
	dst = cvCreateImage(cvGetSize(tmp_frame), 8, 1);
	dst->origin = 1;
			
	if(!tmp_frame)
	{
		//MessageBox("读取视频文件失败，请重新打开真彩色(24位)视频!", "错误信息");
		//return;
	}
	cvNamedWindow("video", 1);
	cvNamedWindow("背景图像", 1);
	cvNamedWindow("前景图像", 1); 
			
	//创建多高斯模型
	CvBGStatModel* bg_model = cvCreateGaussianBGModel(tmp_frame);  
			
	for( int fr = 1;tmp_frame; tmp_frame = cvQueryFrame(m_capture), fr++ )
	{
		cvShowImage("view", tmp_frame);
		//printf("frame# %d : ", fr);
		//获得背景模型更新过程所花费的时间，以 CPU时钟/每微秒 为单位计数
		//double t = (double)cvGetTickCount();  //模型更新之前
				
		cvUpdateBGStatModel( tmp_frame, bg_model );  
		//真正的函数实现体是在: icvUpdateFGDStatModel(tmp_frame, bg_model)
				
		// t = (double)cvGetTickCount() -  t;    //模型更新之后
				
		// 以左下角为坐标原点
		bg_model->foreground->origin = bg_model->background->origin = 1;
				
		//cvErode(bg_model->background, bg_model->background);  
		//滤除噪声
		//cvErode(bg_model->foreground, bg_model->foreground);    
		//滤除噪声
				
		//printf( "%.1f毫秒n", t/(cvGetTickFrequency()*1000.) ); 
		//最后输出结果以毫秒为单位		
		cvShowImage("背景图像", bg_model->background);
		cvCopy(bg_model->foreground, dst);
		cvSmooth(dst, dst, CV_GAUSSIAN, 5);
		cvMorphologyEx( dst, dst, 0, 0, CV_MOP_CLOSE, 3);
		cvMorphologyEx( dst, dst, 0, 0, CV_MOP_OPEN, 1 );
		//提取轮廓 到contour序列中
		//cvFindContours 仅能处理 [单通道、颜色深度为8位的图像] 的轮廓提取
		cvFindContours( dst, m_storage, &m_contour, sizeof(CvContour), CV_RETR_LIST, 
			            CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0));
				
		for( ; m_contour != 0; m_contour = m_contour->h_next )
		{
			CvScalar color = CV_RGB( 255, 0, 255 );
			CvScalar color_rect = CV_RGB( 0, 255, 255);            
					
			m_contour_rect = cvBoundingRect(m_contour, 1); 
					
			/*if(m_contour_rect.height + m_contour_rect.width > 100 && m_contour_rect.width * m_contour_rect.height > 20 && m_contour_rect.height/m_contour_rect.width > 1.5)
			*/
			if(fabs(cvContourArea(m_contour)) > 500.0)
			{ 
			    cvRectangle(dst, cvPoint(m_contour_rect.x, m_contour_rect.y), 
					        cvPoint((m_contour_rect.x + m_contour_rect.width),
							(m_contour_rect.y + m_contour_rect.height)),  color_rect,
							2, 8,  0);  
						
				/* replace CV_FILLED with 1 to see the outlines */  
				cvDrawContours( dst, m_contour, color, color, -1, CV_FILLED, 8, cvPoint(0,0));
				cvShowImage("前景图像",  dst);
				//  cvWaitKey(0);
			}
		}        
		int k = cvWaitKey(1);    //等待一毫秒
		if( k == 'q' ) break;        
	}
			
	cvReleaseBGStatModel( &bg_model );
	cvReleaseCapture(&m_capture);
	cvReleaseImage(&dst);
	if(m_storage) cvClearMemStorage(m_storage);
	cvDestroyWindow("背景图像");
	cvDestroyWindow("前景图像"); 
	return;
}
		

#ifdef _EiC
main(1,"camshiftdemo.c");
#endif