使用OpenCV检测和追踪车辆

完整源码GitHub


使用高斯混合模型（BackgroundSubtractorMOG2）对背景建模，提取出前景
使用中值滤波去掉椒盐噪声，再闭运算和开运算填充空洞
使用cvBlob库追踪车辆，我稍微修改了cvBlob源码来通过编译

由于要对背景建模，这个方法要求背景是静止的

另外不同车辆白色区域不能连通，否则会认为是同一物体

void processVideo(char* videoFilename)
{
Mat frame; // current frame
Mat fgMaskMOG2; // fg mask fg mask generated by MOG2 method
Mat bgImg; // background
Ptr<BackgroundSubtractorMOG2> pMOG2 = createBackgroundSubtractorMOG2(200, 36.0, false); // MOG2 Background subtractor

while (true)
{
VideoCapture capture(videoFilename);
if (!capture.isOpened())
{
cerr << "Unable to open video file: " << videoFilename << endl;
return;
}

int width = (int)capture.get(CV_CAP_PROP_FRAME_WIDTH);
int height = (int)capture.get(CV_CAP_PROP_FRAME_HEIGHT);

unique_ptr<IplImage, void(*)(IplImage*)> labelImg(cvCreateImage(cvSize(width, height), IPL_DEPTH_LABEL, 1),
[](IplImage* p){ cvReleaseImage(&p); });
CvBlobs blobs;
CvTracks tracks;

while (true)
{
// read input data. ESC or 'q' for quitting
int key = waitKey(1);
if (key == 'q' || key == 27)
return;
if (!capture.read(frame))
break;

// update background
pMOG2->apply(frame, fgMaskMOG2);
pMOG2->getBackgroundImage(bgImg);
imshow("BG", bgImg);
imshow("Original mask", fgMaskMOG2);

// post process
medianBlur(fgMaskMOG2, fgMaskMOG2, 5);
imshow("medianBlur", fgMaskMOG2);
morphologyEx(fgMaskMOG2, fgMaskMOG2, MORPH_CLOSE, getStructuringElement(MORPH_RECT, Size(5, 5))); // fill black holes
morphologyEx(fgMaskMOG2, fgMaskMOG2, MORPH_OPEN, getStructuringElement(MORPH_RECT, Size(5, 5))); // fill white holes
imshow("morphologyEx", fgMaskMOG2);

// track
cvLabel(&IplImage(fgMaskMOG2), labelImg.get(), blobs);
cvFilterByArea(blobs, 64, 10000);
cvUpdateTracks(blobs, tracks, 10, 90, 30);
cvRenderTracks(tracks, &IplImage(frame), &IplImage(frame));

// show
imshow("Frame", frame);

key = waitKey(30);
}
}
}