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为了安全起见，我希望能够找到差异b/w 2个类似的灰度图像以用于系统实施。我想检查它们之间是否有差异。对于对象跟踪，我已经在下面的程序中实现了canny检测。我可以很容易地得到结构化对象的轮廓..哪些cn稍后被减去以仅给出三角形图像中差异的轮廓....但是如果在第二图像中存在诸如烟雾或火焰之类的非结构性差异怎么办？我已经增加了更清晰的边缘检测的对比度，以及在canny fn参数中修改了阈值val。但没有得到合适的结果。图像差异：如何找出图像之间的细微差异？
canny边缘也检测阴影边缘。如果我在白天的不同时间拍摄两张相似图像，阴影会有所不同，所以边缘会有所不同，并会产生不希望的虚假警报。
我应该如何解决此问题？谁能帮忙？谢谢！ 在enter code here OpenCV的2.4使用Visual Studio中的C语言API 2010
#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);
}
您忘记了添加代码。 **编辑**的问题添加代码 – 2013-04-26 11:20:25
哦，是的，我的坏。 – 2013-04-26 11:53:08