OpenCV实现简单摄像头视频监控程序

#include <cv.h>#include <time.h>#include <stdio.h>#include <stdlib.h>#include <highgui.h> #define ESC 0x1b #define TRUE 1#define FALSE 0 // 检测图像异常，仅在采样时调用。// 返回真表示已检测到异常，需要重新采样。// 返回假表示未检测到异常，在一定时间后即可获取基准图像。int detect(CvCapture* capture, IplImage* std, IplImage* frm, CvRect* rect); // 图像采样，确定基准图像，以便监测场景变化// 返回真表示采样成功，返回假表示采样失败int gather(CvCapture* capture, IplImage* std, CvRect* rect); // 摄像机监视，用矩形框标示出和基准图像反差较大的图像范围。void monitor(CvCapture* capture, IplImage* std, CvRect* rect); // 求 x 的平方int square(int x); int main(int argc, char* argv[]){ CvCapture* capture;   // 摄像机源 IplImage* std;     // 基准图像 CvRect rect;      // 异常位置矩形标识  capture = cvCreateCameraCapture(0); if (!capture) return -1;  std = cvQueryFrame(capture); rect = cvRect(-1, -1, 0, 0);  std = cvCloneImage(std);  cvNamedWindow("Monitor Screen");  if (gather(capture, std, &rect)) { monitor(capture, std, &rect); }  cvDestroyWindow("Monitor Screen"); cvReleaseImage(&std); cvReleaseCapture(&capture);  return 0;} int detect(CvCapture* capture, IplImage* std, IplImage* frm, CvRect* rect){ int x, y;            // 循环变量 int f = FALSE;         // 检测到异常的标识 int x1 = -1, x2 = 0;      // 异常区域矩形横坐标范围 int y1 = -1, y2 = 0;      // 异常区域矩形纵坐标范围  uchar *ptr1b, *ptr1g, *ptr1r;  // 基准图像的每个像素的三个颜色通道的值 uchar *ptr2b, *ptr2g, *ptr2r;  // 实时图像的每个像素的三个颜色通道的值  int squaresum;         // 计算 RGB 差值平方和  // 遍历图像中的每一个点，将实时采样图与基准图做比较，检测两者的每一个 // 像素点的 RGB 差值平方和。当该值大于 8192 时（换算成灰度值则意味着 // 两者的灰度差大于 90）则立即报告出现异常，只有遍历完毕后仍未找到异 // 常才报告没有异常。  for (y = 0; y < std->height; y++) { for (x = 0; x < std->width; x++) {  ptr1b = cvPtr2D(std, y, x) + 0; ptr2b = cvPtr2D(frm, y, x) + 0;  ptr1g = cvPtr2D(std, y, x) + 1; ptr2g = cvPtr2D(frm, y, x) + 1;  ptr1r = cvPtr2D(std, y, x) + 2; ptr2r = cvPtr2D(frm, y, x) + 2;   squaresum =  square(*ptr1b - *ptr2b) +  square(*ptr1g - *ptr2g) +  square(*ptr1r - *ptr2r);   if (squaresum > 8192)  {  if (f)  {   if (x < x1) x1 = x; else if (x > x2) x2 = x;   if (y < y1) y1 = y; else if (y > y2) y2 = y;  }  else  {   f = TRUE;    x1 = x; y1 = y;   x2 = x; y2 = y;  }  } } }  if (x2 - x1 > frm->width / 4 || y2 - y1 > frm->height / 4) { f = TRUE; } else { f = FALSE; }  *rect = cvRect(x1, y1, x2 - x1, y2 - y1); return f;} int gather(CvCapture* capture, IplImage* std, CvRect* rect){ IplImage* frm; int except = FALSE;       // 检测到异常的标识 int finish = FALSE;       // 采样已完成的标识 clock_t start_time, real_time; // 时间段监测  start_time = clock();  while (!finish) { frm = cvQueryFrame(capture); cvShowImage("Monitor Screen", frm);  except = detect(capture, std, frm, rect);  if (except) {  start_time = clock();  cvCopyImage(frm, std); }  if (cvWaitKey(15) == ESC) break;  real_time = clock(); if (real_time - start_time >= 3000) {  finish = TRUE; } }  return finish;} void monitor(CvCapture* capture, IplImage* std, CvRect* rect){ IplImage* frm; int except = FALSE; int finish = FALSE;  while (!finish) { frm = cvQueryFrame(capture);  except = detect(capture, std, frm, rect);  if (except) {  cvRectangle(  frm,  cvPoint(rect->x, rect->y),  cvPoint(rect->x + rect->width, rect->y + rect->height),  cvScalar(0, 0, 255),  4); } cvShowImage("Monitor Screen", frm);  if (cvWaitKey(15) == ESC) {  finish = TRUE; } }} int square(int x){ return x * x;}