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平均背景法的基本思想是計算每個像素的平均值和標準差作為它的背景模型。
平均背景法使用四個OpenCV函數:
代碼:
/* 平均背景法 */ #include "highgui.h" #include "cv.h" #include<stdlib.h> #include<stdio.h> //為不同的臨時指針圖像和統計屬性創建指針 //Float, 3-channel images IplImage* IavgF, * IdiffF, * IprevF, * IhiF, *IlowF; IplImage* Iscratch, *Iscratch3; //Float 1-channel images IplImage* Igray1, * Igray2, * Igray3; IplImage* Ilow1, * Ilow2, * Ilow3; IplImage* Ihi1, *Ihi2, * Ihi3; //Byte, 1-channel image IplImage* Imask; IplImage* Imaskt; //Counts number of images learned for averaging later. float Icount; // 創建一個函數來給需要的所有臨時圖像分配內存 //為了方便,我們傳遞一幅圖像(來自視頻)作為大小參考來分配臨時圖像 void AllocateImages(IplImage* I) { CvSize sz = cvGetSize(I); IavgF = cvCreateImage(sz, IPL_DEPTH_32F, 3); IdiffF = cvCreateImage(sz, IPL_DEPTH_32F,3); IprevF = cvCreateImage(sz, IPL_DEPTH_32F,3); IhiF = cvCreateImage(sz, IPL_DEPTH_32F, 3); IlowF = cvCreateImage(sz, IPL_DEPTH_32F,3); Ilow1 = cvCreateImage(sz, IPL_DEPTH_32F,1); Ilow2 = cvCreateImage(sz, IPL_DEPTH_32F,1); Ilow3 = cvCreateImage(sz, IPL_DEPTH_32F,1); Ihi1 = cvCreateImage(sz, IPL_DEPTH_32F,1); Ihi2 = cvCreateImage(sz, IPL_DEPTH_32F,1); Ihi3 = cvCreateImage(sz, IPL_DEPTH_32F,1); cvZero(IavgF); cvZero(IdiffF); cvZero(IprevF); cvZero(IhiF); cvZero(IlowF); Icount = 0.00001; Iscratch = cvCreateImage(sz, IPL_DEPTH_32F,3); Iscratch3 = cvCreateImage(sz, IPL_DEPTH_32F,3); Igray1 = cvCreateImage(sz, IPL_DEPTH_32F,1); Igray2 = cvCreateImage(sz, IPL_DEPTH_32F,1); Igray3 = cvCreateImage(sz, IPL_DEPTH_32F,1); Imask = cvCreateImage(sz, IPL_DEPTH_8U, 1); Imaskt = cvCreateImage(sz, IPL_DEPTH_8U,1); cvZero(Iscratch); cvZero(Iscratch3); } //學習累積背景圖像和每一幀圖像差值的絕對值 // Learn the background statistics for one more frame // I is a color sample of the background, 3-channel, 8u void accumulateBackground(IplImage *I) { static int first = 1; cvCvtScale(I, Iscratch, 1, 0); if(!first) { cvAcc(Iscratch,IavgF); cvAbsDiff(Iscratch, IprevF, Iscratch3); cvAcc(Iscratch3,IdiffF); Icount += 1.0; } first = 0; cvCopy(Iscratch, IprevF); } //setHighThreshold和setLowThreshold都是基于每一幀圖像平均絕對差設置閾值的有效函數 void setHighThreshold(float scale) { cvConvertScale(IdiffF, Iscratch, scale); cvAdd(Iscratch, IavgF, IhiF); cvSplit(IhiF, Ihi1, Ihi2, Ihi3, 0); } void setLowThreshold(float scale) { cvConvertScale(IdiffF, Iscratch, scale); cvSub(IavgF, Iscratch, IlowF); cvSplit(IlowF, Ilow1, Ilow2, Ilow3, 0); } //當積累了足夠多的幀圖像之后,就將其轉化為一個背景的統計模型 //計算每一個像素的均值和方差觀測 void createModelsfromStats() { cvConvertScale(IavgF, IavgF, (double)(1.0/Icount)); cvConvertScale(IdiffF, IdiffF, (double)(1.0/Icount)); //Make sure diff is always something cvAddS(IdiffF, cvScalar(1.0, 1.0, 1.0), IdiffF); setHighThreshold(7.0); setLowThreshold(6.0); } //有了背景模型,同時給出了高,低閾值,就能用它將圖像分割為前景和背景 // Create a binary: 0,255 mask where 255 means foregrond pixel // I Input image, 3-channel, 8u //Imask void backgroundDiff(IplImage* I) { cvCvtScale(I, Iscratch, 1, 0); cvSplit(Iscratch, Igray1, Igray2, Igray3, 0); //Channel 1 cvInRange(Igray1, Ilow1, Ihi1, Imask); //Channel 2 cvInRange(Igray2, Ilow2, Ihi2, Imaskt); cvOr(Imask, Imaskt, Imask); //Channel 3 cvInRange(Igray3, Ilow3, Ihi3, Imaskt); cvOr(Imask, Imaskt, Imask); //Finally, invert the result cvSubRS(Imask, cvScalar(255), Imask); } //完成背景建模后, 釋放內存 void DeallocateImage() { cvReleaseImage(&IavgF); cvReleaseImage(&IdiffF); cvReleaseImage(&IprevF); cvReleaseImage(&IhiF); cvReleaseImage(&IlowF); cvReleaseImage(&Ilow1); cvReleaseImage(&Ilow2); cvReleaseImage(&Ilow3); cvReleaseImage(&Iscratch); cvReleaseImage(&Iscratch3); cvReleaseImage(&Igray1); cvReleaseImage(&Igray2); cvReleaseImage(&Igray3); cvReleaseImage(&Imaskt); } //主函數 int main() { CvCapture* capture = cvCreateFileCapture("tree.avi"); if(!capture) { return -1; } cvNamedWindow("win1"); cvNamedWindow("win2"); IplImage* rawImage = cvQueryFrame(capture); cvShowImage("win1", rawImage); AllocateImages(rawImage); int i = 0; while(1) { if(i <= 30) { accumulateBackground(rawImage); if(i == 30) { createModelsfromStats(); } } else { backgroundDiff(rawImage); } cvShowImage("win2", Imask); if(cvWaitKey(33) == 27) { break; } if(!(rawImage = cvQueryFrame(capture))) { break; } cvShowImage("win1", rawImage); if(i == 56 || i == 63) cvWaitKey(); i = i+1; } DeallocateImage(); return 0; }
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