为了安全起见，我想找到 hwo 以获得 diff b/w 2 个类似的灰度图像，以便在系统中实现。我想检查它们之间是否发生了任何差异。对于对象跟踪，我在下面的程序中实现了精明检测。我很容易得到结构化对象的轮廓.. 后来减去 cn 以仅给出增量图像中差异的轮廓....但是如果第二张图像中存在非结构性差异（例如烟雾或火）怎么办？我增加了对比度以获得更清晰的边缘检测，并修改了 canny fn 参数中的阈值 vals..但没有得到合适的结果。
canny edge 也可以检测阴影边缘。如果我的两张相似的图像是在一天中的不同时间拍摄的，阴影会有所不同，因此边缘会有所不同，并且会产生不良的误报
我应该如何解决这个问题？任何人都可以帮忙吗？谢谢！enter code here在 Visual Studio 2010 的 opencv 2.4 中使用 c 语言 api
#include "stdafx.h"
#include "cv.h"
#include "highgui.h"
#include "cxcore.h"
#include <math.h>
#include <iostream>
#include <stdio.h>
using namespace cv;
using namespace std;
int main()
{
IplImage* img1 = NULL;
if ((img1 = cvLoadImage("libertyH1.jpg"))== 0)
{
printf("cvLoadImage failed\n");
}
IplImage* gray1 = cvCreateImage(cvGetSize(img1), IPL_DEPTH_8U, 1); //contains greyscale //image
CvMemStorage* storage1 = cvCreateMemStorage(0); //struct for storage
cvCvtColor(img1, gray1, CV_BGR2GRAY); //convert to greyscale
cvSmooth(gray1, gray1, CV_GAUSSIAN, 7, 7); // This is done so as to //prevent a lot of false circles from being detected
IplImage* canny1 = cvCreateImage(cvGetSize(gray1),IPL_DEPTH_8U,1);
IplImage* rgbcanny1 = cvCreateImage(cvGetSize(gray1),IPL_DEPTH_8U,3);
cvCanny(gray1, canny1, 50, 100, 3); //cvCanny( const //CvArr* image, CvArr* edges(output edge map), double threshold1, double threshold2, int //aperture_size CV_DEFAULT(3) );
cvNamedWindow("Canny before hough");
cvShowImage("Canny before hough", canny1);
CvSeq* circles1 = cvHoughCircles(gray1, storage1, CV_HOUGH_GRADIENT, 1, gray1->height/3, 250, 100);
cvCvtColor(canny1, rgbcanny1, CV_GRAY2BGR);
cvNamedWindow("Canny after hough");
cvShowImage("Canny after hough", rgbcanny1);
for (size_t i = 0; i < circles1->total; i++)
{
// round the floats to an int
float* p = (float*)cvGetSeqElem(circles1, i);
cv::Point center(cvRound(p[0]), cvRound(p[1]));
int radius = cvRound(p[2]);
// draw the circle center
cvCircle(rgbcanny1, center, 3, CV_RGB(0,255,0), -1, 8, 0 );
// draw the circle outline
cvCircle(rgbcanny1, center, radius+1, CV_RGB(0,0,255), 2, 8, 0 );
printf("x: %d y: %d r: %d\n",center.x,center.y, radius);
}
//////////////////////////////////////////////////////////////////////////////////////////////////////////////
IplImage* img2 = NULL;
if ((img2 = cvLoadImage("liberty_wth_obj.jpg"))== 0)
{
printf("cvLoadImage failed\n");
}
IplImage* gray2 = cvCreateImage(cvGetSize(img2), IPL_DEPTH_8U, 1);
CvMemStorage* storage = cvCreateMemStorage(0);
cvCvtColor(img2, gray2, CV_BGR2GRAY);
// This is done so as to prevent a lot of false circles from being detected
cvSmooth(gray2, gray2, CV_GAUSSIAN, 7, 7);
IplImage* canny2 = cvCreateImage(cvGetSize(img2),IPL_DEPTH_8U,1);
IplImage* rgbcanny2 = cvCreateImage(cvGetSize(img2),IPL_DEPTH_8U,3);
cvCanny(gray2, canny2, 50, 100, 3);
CvSeq* circles2 = cvHoughCircles(gray2, storage, CV_HOUGH_GRADIENT, 1, gray2->height/3, 250, 100);
cvCvtColor(canny2, rgbcanny2, CV_GRAY2BGR);
for (size_t i = 0; i < circles2->total; i++)
{
// round the floats to an int
float* p = (float*)cvGetSeqElem(circles2, i);
cv::Point center(cvRound(p[0]), cvRound(p[1]));
int radius = cvRound(p[2]);
// draw the circle center
cvCircle(rgbcanny2, center, 3, CV_RGB(0,255,0), -1, 8, 0 );
// draw the circle outline
cvCircle(rgbcanny2, center, radius+1, CV_RGB(0,0,255), 2, 8, 0 );
printf("x: %d y: %d r: %d\n",center.x,center.y, radius);
}