Static background substraction

Static background substraction adalah metode untuk mengetahui perbedaan antara dua frame dimana frame pertama digunakan sebagai background dan frame kedua sebagai masukan dapat berupa frame tetap atau frame yang berubah ubah.Contoh ilustrasi dari static background substraction seperti berikut ini.

 

Berikut ini adalah program dari static background substraction dan video hasil static background substraction.

PROGRAM

#include <stdlib.h> #include <string> #include <cstring> #include <iostream> #include <string.h> #include <stdio.h> #include <math.h> #include "cv.h" #include "highgui.h" using namespace std; int thresh = 50; int max_thresh = 300; int main(int argc, char* argv[]) {     CvCapture* capture = cvCaptureFromCAM(0);     if ( !capture ) {         fprintf( stderr, "ERROR: capture is NULL \n" );         getchar();         return -1;                      }     // Create a window in which the captured images will be presented     cvNamedWindow( "reference", CV_WINDOW_AUTOSIZE );     // Show the image captured from the camera in the window and repeat     cvNamedWindow( "background", CV_WINDOW_AUTOSIZE );     cvNamedWindow( "difference", CV_WINDOW_AUTOSIZE );     cvNamedWindow( "canny edge", CV_WINDOW_AUTOSIZE );     cvNamedWindow( "res", CV_WINDOW_AUTOSIZE );     //load background template     IplImage* tpl = cvLoadImage("background.jpg");     IplImage* gtpl = cvCreateImage(cvGetSize(tpl), IPL_DEPTH_8U, 1);     while (1) {             IplImage *img= cvQueryFrame(capture);             if(!img) break;             IplImage* gIn = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);             IplImage* differenceImg = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);             cvCvtColor (tpl, gtpl, CV_BGR2GRAY );             cvCvtColor (img, gIn, CV_BGR2GRAY );             //3. Cari perbedaan background             //Minus the current frame from the moving average.             cvAbsDiff(gtpl,gIn,differenceImg);                      //treshold             cvCreateTrackbar( " Threshold input:", "difference", &thresh, max_thresh, NULL );             cvThreshold(differenceImg, differenceImg,thresh, 255, CV_THRESH_BINARY );  //nilai trail and error             //cvAdaptiveThreshold(differenceImg,differenceImg,255,CV_ADAPTIVE_THRESH_GAUSSIAN_C,CV_THRESH_BINARY,3,5);             //mode : CV_ADAPTIVE_THRESH_GAUSSIAN_C atau CV_ADAPTIVE_THRESH_MEAN_C              //4. Gunakan metode canny edge             IplImage* cannyImg = cvCreateImage(cvGetSize(gIn), IPL_DEPTH_8U, 1);             //5. Filter             cvCanny(differenceImg, cannyImg, 50, 150, 3);             cvDilate(cannyImg,cannyImg,NULL,1);             cvErode(cannyImg,cannyImg,NULL,1);                 cvShowImage( "reference", img);             cvShowImage( "background", tpl);             cvShowImage( "difference", cannyImg);             if ( (cvWaitKey(10) & 255) == 27 ) break;     }     //deallocate windows     cvDestroyWindow( "reference" );     cvDestroyWindow( "background" );     cvDestroyWindow( "difference" );     //deallocate images     cvReleaseImage(&tpl);     cvReleaseCapture ( &capture );     return 0; }

 

VIDEO