OpenCV学习之运动模板检测

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运动模板检测
#include "cv.h"#include "highgui.h"#include <time.h>  #include <math.h>  #include <ctype.h>  #include <stdio.h>  // 不同的跟踪参数  const double MHI_DURATION = 0.5;const double MAX_TIME_DELTA = 0.5;const double MIN_TIME_DELTA = 0.05;// 用于运动检测的循环帧数，与机器速度及FPS设置有关  const int N = 2;IplImage **buf = 0;int last = 0;// 临时图像  IplImage *mhi = 0; // MHI: 运动历史图像  IplImage *orient = 0; // 方向  IplImage *mask = 0; // 有效的运动掩码  IplImage *segmask = 0; // 运动分割映射  CvMemStorage* storage = 0; // 临时存储区                             // parameters:                             //  img - input video frame                             //  dst - resultant motion picture                             //  args - optional parameters  void  update_mhi(IplImage* img, IplImage* dst, int diff_threshold) {    double timestamp = clock() / 1000.; // 获取当前时间,以秒为单位      CvSize size = cvSize(img->width, img->height); // 获取当前帧尺寸      int i, idx1 = last, idx2;    IplImage* silh;    CvSeq* seq;    CvRect comp_rect;    double count;    double angle;    CvPoint center;    double magnitude;    CvScalar color;    // 开始时为图像分配内存 or 帧尺寸改变时重新分配内存      if (!mhi || mhi->width != size.width || mhi->height != size.height) {        if (buf == 0) {            buf = (IplImage**)malloc(N * sizeof(buf[0]));            memset(buf, 0, N * sizeof(buf[0]));        }        for (i = 0; i < N; i++) {            cvReleaseImage(&buf[i]);            buf[i] = cvCreateImage(size, IPL_DEPTH_8U, 1);            cvZero(buf[i]);        }        cvReleaseImage(&mhi);        cvReleaseImage(&orient);        cvReleaseImage(&segmask);        cvReleaseImage(&mask);        mhi = cvCreateImage(size, IPL_DEPTH_32F, 1);        cvZero(mhi); // clear MHI at the beginning          orient = cvCreateImage(size, IPL_DEPTH_32F, 1);        segmask = cvCreateImage(size, IPL_DEPTH_32F, 1);        mask = cvCreateImage(size, IPL_DEPTH_8U, 1);    }    cvCvtColor(img, buf[last], CV_BGR2GRAY); //RGB帧图像格式转换为gray      idx2 = (last + 1) % N; // index of (last - (N-1))th frame      last = idx2;    silh = buf[idx2];    // 相邻两帧的差      cvAbsDiff(buf[idx1], buf[idx2], silh);    cvThreshold(silh, silh, diff_threshold, 1, CV_THRESH_BINARY); // 对差图像做二值化      cvUpdateMotionHistory(silh, mhi, timestamp, MHI_DURATION); // 更新运动历史                                                                 // convert MHI to blue 8u image                                                                 // cvCvtScale的第四个参数 shift = (MHI_DURATION - timestamp)*255./MHI_DURATION                                                                 // 控制帧差的消失速率      cvCvtScale(mhi, mask, 255. / MHI_DURATION,        (MHI_DURATION - timestamp)*255. / MHI_DURATION);    cvZero(dst);    cvCvtPlaneToPix(mask, 0, 0, 0, dst);  // B,G,R,0 convert to BLUE image                                            // 计算运动的梯度方向以及正确的方向掩码                                            // Filter size = 3      cvCalcMotionGradient(mhi, mask, orient,        MAX_TIME_DELTA, MIN_TIME_DELTA, 3);    if (!storage)        storage = cvCreateMemStorage(0);    else        cvClearMemStorage(storage);    // 运动分割： 获得运动部件的连续序列      seq = cvSegmentMotion(mhi, segmask, storage, timestamp, MAX_TIME_DELTA);    for (i = 0; i < seq->total; i++) {        if (i < 0) {        // 对整幅图像操作              comp_rect = cvRect(0, 0, size.width, size.height);            color = CV_RGB(255, 255, 255);            magnitude = 100;  // 画线长度以及圆半径的大小控制          }        else {          // 第i个运动组件              comp_rect = ((CvConnectedComp*)cvGetSeqElem(seq, i))->rect;            // 去掉小的部分              if (comp_rect.width + comp_rect.height < 100)                continue;            color = CV_RGB(255, 0, 0);            magnitude = 30;            //if(seq->total > 0) MessageBox(NULL,"Motion Detected",NULL,0);          }        // 选择组件ROI          cvSetImageROI(silh, comp_rect);        cvSetImageROI(mhi, comp_rect);        cvSetImageROI(orient, comp_rect);        cvSetImageROI(mask, comp_rect);        // 在选择的区域内，计算运动方向          angle = cvCalcGlobalOrientation(orient, mask, mhi, timestamp,            MHI_DURATION);        angle = 360.0 - angle;  // adjust for images with top-left origin                                  // 在轮廓内计算点数                                  // Norm(L1) = 所有像素值的和          count = cvNorm(silh, 0, CV_L1, 0);        cvResetImageROI(mhi);        cvResetImageROI(orient);        cvResetImageROI(mask);        cvResetImageROI(silh);        // 检查小运动的情形          if (count < comp_rect.width*comp_rect.height * 0.05)  //  像素的5%              continue;        // 画一个带箭头的记录以表示方向          center = cvPoint((comp_rect.x + comp_rect.width / 2),            (comp_rect.y + comp_rect.height / 2));        cvCircle(dst, center, cvRound(magnitude*1.2), color, 3, CV_AA, 0);        cvLine(dst, center, cvPoint(cvRound(center.x +            magnitude*cos(angle*CV_PI / 180)),            cvRound(center.y - magnitude*sin(angle*CV_PI / 180))),            color, 3, CV_AA, 0);    }}int main(int argc, char** argv) {    IplImage* motion = 0;    CvCapture* capture = 0;    if (argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))        capture = cvCaptureFromCAM(argc == 2 ? argv[1][0] - '0' : 0);    else if (argc == 2)        capture = cvCaptureFromAVI(argv[1]);    if (capture) {        cvNamedWindow("Motion", 1);        for (;;) {            IplImage* image;            if (!cvGrabFrame(capture))                break;            image = cvRetrieveFrame(capture);            if (image) {                if (!motion) {                    motion = cvCreateImage(cvSize(image->width, image->height),                        8, 3);                    cvZero(motion);                    motion->origin = image->origin;                }            }            update_mhi(image, motion, 60);            cvShowImage("Motion", motion);            if (cvWaitKey(10) >= 0)                break;        }        cvReleaseCapture(&capture);        cvDestroyWindow("Motion");    }    return 0;}
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