opencv学习1 还有附带的kalman滤波

标配opencv头文件

#include <opencv2/core/core.hpp>  
#include<opencv2/highgui/highgui.hpp>  
   
using namespace cv;  

</pre><pre name="code" class="cpp">

在vs2010中运行vc6.0的文件，可以直接将其拷贝到新的Cpp文件中，当然指的是控制台系统，至于mfc就不会拷贝，

下图为kalman滤波代码，直接拷贝就可以运行。

#include "cv.h"
#include "highgui.h"
#include <math.h>


int main(int argc, char** argv)
{
    /* A matrix data */
    const float A[] = { 1, 1, 0, 1 };


    IplImage* img = cvCreateImage( cvSize(500,500), 8, 3 );
    CvKalman* kalman = cvCreateKalman( 2, 1, 0 );
    /* state is (phi, delta_phi) - angle and angle increment */
    CvMat* state = cvCreateMat( 2, 1, CV_32FC1 );
    CvMat* process_noise = cvCreateMat( 2, 1, CV_32FC1 );
    /* only phi (angle) is measured */
    CvMat* measurement = cvCreateMat( 1, 1, CV_32FC1 );
    CvRandState rng;
    int code = -1;


    cvRandInit( &rng, 0, 1, -1, CV_RAND_UNI );


    cvZero( measurement );
    cvNamedWindow( "Kalman", 1 );


    for(;;)
    {
        cvRandSetRange( &rng, 0, 0.1, 0 );
        rng.disttype = CV_RAND_NORMAL;


        cvRand( &rng, state );


        memcpy( kalman->transition_matrix->data.fl, A, sizeof(A));
        cvSetIdentity( kalman->measurement_matrix, cvRealScalar(1) );
        cvSetIdentity( kalman->process_noise_cov, cvRealScalar(1e-5) );
        cvSetIdentity( kalman->measurement_noise_cov, cvRealScalar(1e-1) );
        cvSetIdentity( kalman->error_cov_post, cvRealScalar(1));
        /* choose random initial state */
        cvRand( &rng, kalman->state_post );


        rng.disttype = CV_RAND_NORMAL;


        for(;;)
        {
            #define calc_point(angle)                                      \
                cvPoint( cvRound(img->width/2 + img->width/3*cos(angle)),  \
                         cvRound(img->height/2 - img->width/3*sin(angle)))


            float state_angle = state->data.fl[0];
            CvPoint state_pt = calc_point(state_angle);


            /* predict point position */
            const CvMat* prediction = cvKalmanPredict( kalman, 0 );
            float predict_angle = prediction->data.fl[0];
            CvPoint predict_pt = calc_point(predict_angle);
            float measurement_angle;
            CvPoint measurement_pt;


cvRandSetRange( &rng, 0, 
sqrt(kalman->measurement_noise_cov->data.fl[0]), 0 );
            cvRand( &rng, measurement );


            /* generate measurement */
cvMatMulAdd( kalman->measurement_matrix, 
state, measurement, measurement );


            measurement_angle = measurement->data.fl[0];
            measurement_pt = calc_point(measurement_angle);


            /* plot points */
            #define draw_cross( center, color, d )                                 \
                cvLine( img, cvPoint( center.x - d, center.y - d ),                \
                             cvPoint( center.x + d, center.y + d ), color, 1, 0 ); \
                cvLine( img, cvPoint( center.x + d, center.y - d ),                \
                             cvPoint( center.x - d, center.y + d ), color, 1, 0 )


            cvZero( img );
            draw_cross( state_pt, CV_RGB(255,255,255), 3 );
            draw_cross( measurement_pt, CV_RGB(255,0,0), 3 );
            draw_cross( predict_pt, CV_RGB(0,255,0), 3 );
            cvLine( img, state_pt, predict_pt, CV_RGB(255,255,0), 3, 0 );


            /* adjust Kalman filter state */
            cvKalmanCorrect( kalman, measurement );


            cvRandSetRange( &rng, 0, sqrt(kalman->process_noise_cov->data.fl[0]), 0 );
            cvRand( &rng, process_noise );
            cvMatMulAdd( kalman->transition_matrix, state, process_noise, state );


            cvShowImage( "Kalman", img );
            code = cvWaitKey( 100 );


            if( code > 0 ) /* break current simulation by pressing a key */
                break;
        }
        if( code == 27 ) /* exit by ESCAPE */
            break;
    }


    return 0;
}