我有一个处理图像的功能。在该函数中，我试图找到几个特定的省略号。如果我在一个单独的项目中单独调用它，代码就可以正常工作，但在整个项目中，它会在返回时崩溃。
我在处理过程中使用了很多向量来存储过程中的一些信息。
错误信息：
Windows has triggered a breakpoint in KinectBridgeWithOpenCVBasics-D2D.exe.
This may be due to a corruption of the heap, which indicates a bug in KinectBridgeWithOpenCVBasics-D2D.exe or any of the DLLs it has loaded.
This may also be due to the user pressing F12 while KinectBridgeWithOpenCVBasics-D2D.exe has focus.
The output window may have more diagnostic information.
任何人都可以告诉我造成这次崩溃的错误。更奇怪的是，它正在单独的项目中工作。
代码有点长，但实际上是注意到，只是寻找带有某种模式的几个特殊椭圆。
谢谢。
int FindNao(Mat* pImg, double* x, double* y)
{
// Fail if pointer is invalid
if (!pImg)
{
return 2;
}
// Fail if Mat contains no data
if (pImg->empty())
{
return 3;
}
//*x = 0; *y = 0;
Mat localMat = *pImg; // save a local copy of the image
cvtColor(~localMat, localMat, CV_BGR2GRAY); // Convert to gray image
threshold(localMat, localMat, 165, 255, THRESH_BINARY); // Convert into black-white image
Mat elementOpen = getStructuringElement(MORPH_ELLIPSE, Size(5,5), Point(-1,-1));
morphologyEx(localMat, localMat, MORPH_OPEN, elementOpen, Point(-1,-1), 1);
// Find all the contours in the blak-white image
vector<vector<Point>> contours;
findContours(localMat.clone(), contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
localMat.release();
// Calculate the area of each contour
vector<double> areas; int num = contours.size();
/* If no contours are found, return S_OK */
if(num < 1)
return 1;
for(int i = 0; i < num; i++)
{
areas.push_back(contourArea(contours[i]));
}
// First round of selection
// The area is small, and they are like a ellipse and around the middle in X direction and at the upper part of the image
vector<RotatedRect> selected_ellipses; // store the fitted ellipse fitted to the potential contour
vector<double> selected_areas; // store the contour area of the potential contour
int imgX = localMat.cols; int imgY = localMat.rows; // get the demension of the image
for(int i=0; i < num - 1; i++)
{
if(areas[i] < 350 && areas[i] > 10)
{
// fit an ellipse
RotatedRect ellipse1 = fitEllipse(Mat(contours[i]));
// it is a reasonable ellipse, and the area should be close to the
double length1 = ellipse1.size.height;
double length2 = ellipse1.size.width;
if( abs(1 - length1/length2) <= 0.8 &&
abs(1 - areas[i] / (CV_PI * length1 * length2 / 4) ) <= 0.2 )
{
selected_ellipses.push_back(ellipse1);
selected_areas.push_back(areas[i]);
}
}
}
/************ Second round of selection **************/
// Calculate each ellipse's dimension
vector<double> diff_dimension;
vector<double> ave_dimention;
/* If no contours are found, return S_OK */
if(selected_ellipses.size() < 1)
return 1;
for(int i = 0; i < selected_ellipses.size(); i++)
{
double difference = abs(1 - selected_ellipses[i].size.height / selected_ellipses[i].size.width);
diff_dimension.push_back(difference);
double average = (selected_ellipses[i].size.height + selected_ellipses[i].size.width) / 2;
ave_dimention.push_back(average);
}
vector<vector<int>> eyematches;
vector<vector<int>> cammatches;
// go over all the ellipses to find the matches with close area and dimension.
for(int i = 0; i < selected_ellipses.size() - 1; i++)
{
for(int j = i+1; j < selected_ellipses.size(); j++)
{
// looking for the eyes
if(diff_dimension[i] < 0.05 && diff_dimension[j] < 0.05)
{
double diff_area = abs( 1 - selected_areas[i] / selected_areas[j] );
if (diff_area < 0.05)
{
double diff_y = abs(selected_ellipses[i].center.y - selected_ellipses[j].center.y);
if(diff_y < 10)
{
vector<int> match1;
match1.push_back(i); match1.push_back(j);
eyematches.push_back(match1);
}
}
}
// looking for the cameras
double diff_x = abs(selected_ellipses[i].center.x - selected_ellipses[j].center.x);
if (diff_x < 10)
{
vector<int> match2;
match2.push_back(i); match2.push_back(j);
cammatches.push_back(match2);
}
}
}
/* Last check */
int num_eyes = eyematches.size();
int num_cams = cammatches.size();
if(num_eyes == 0 || num_cams == 0)
return 1;
// Calculate the vector between two eyes and the center
vector<Point> vector_eyes; vector<Point> center_eyes;
vector<vector<int>>::iterator ite = eyematches.begin();
while(ite < eyematches.end())
{
Point point;
point.x = selected_ellipses[(*ite)[0]].center.x - selected_ellipses[(*ite)[1]].center.x;
point.y = selected_ellipses[(*ite)[0]].center.y - selected_ellipses[(*ite)[1]].center.y;
vector_eyes.push_back(point);
point.x = (selected_ellipses[(*ite)[0]].center.x + selected_ellipses[(*ite)[1]].center.x)/2;
point.y = (selected_ellipses[(*ite)[0]].center.y + selected_ellipses[(*ite)[1]].center.y)/2;
center_eyes.push_back(point);
ite++;
}
// Calculate the vector between two cameras and the center
vector<Point> vector_cams; vector<Point> center_cams;
ite = cammatches.begin();
while(ite < cammatches.end())
{
Point point;
point.x = selected_ellipses[(*ite)[0]].center.x - selected_ellipses[(*ite)[1]].center.x;
point.y = selected_ellipses[(*ite)[0]].center.y - selected_ellipses[(*ite)[1]].center.y;
vector_cams.push_back(point);
point.x = (selected_ellipses[(*ite)[0]].center.x + selected_ellipses[(*ite)[1]].center.x)/2;
point.y = (selected_ellipses[(*ite)[0]].center.y + selected_ellipses[(*ite)[1]].center.y)/2;
center_cams.push_back(point);
ite++;
}
// Match the eyes and cameras, by calculating the center distances and intersection angle
vector<vector<int>> matches_eye_cam;
vector<vector<double>> matches_parameters;
for(int i = 0; i < num_eyes; i++)
{
for(int j = 0; j < num_cams; j++)
{
vector<int> temp1;
vector<double> temp2;
// calculate the distances
double distance = sqrt( double( (center_eyes[i].x - center_cams[j].x)^2 + (center_eyes[i].y - center_cams[j].y)^2 ) );
// calculate the cosine intersection angle
double cosAngle = vector_eyes[i].x * vector_cams[j].x + vector_eyes[i].y * vector_cams[j].y;
// store everything
temp1.push_back(i); temp1.push_back(j);
temp2.push_back(distance); temp2.push_back(cosAngle);
matches_eye_cam.push_back(temp1);
matches_parameters.push_back(temp2);
}
}
// go over to find the minimum
int min_dis = 0; int min_angle = 0;
vector<vector<double>>::iterator ite_para = matches_parameters.begin();
/* If no contours are found, return S_OK */
if(matches_parameters.size() < 1)
return 1;
for(int i = 1; i < matches_parameters.size(); i++)
{
if( (*(ite_para+min_dis))[0] > (*(ite_para+i))[0] )
min_dis = i;
if( (*(ite_para+min_angle))[1] > (*(ite_para+i))[1] )
min_angle = i;
}
// get the best match of eyes and cameras 's index
int eyes_index, cams_index;
vector<vector<int>>::iterator ite_match_eye_cam = matches_eye_cam.begin();
if(min_dis == min_angle)
{
// perfect match
eyes_index = (*(ite_match_eye_cam + min_dis))[0];
cams_index = (*(ite_match_eye_cam + min_dis))[1];
}
else
{
// tried to fuse them and find a better sulotion, but didnot work out, so
// go with the min_dis
eyes_index = (*(ite_match_eye_cam + min_dis))[0];
cams_index = (*(ite_match_eye_cam + min_dis))[1];
}
vector<vector<int>>::iterator ite_eyes = eyematches.begin();
vector<vector<int>>::iterator ite_cams = cammatches.begin();
// draw the eyes
ellipse(*pImg, selected_ellipses[(*(ite_eyes+eyes_index))[0]], Scalar(0, 255, 255), 2, 8);
ellipse(*pImg, selected_ellipses[(*(ite_eyes+eyes_index))[1]], Scalar(0, 255, 255), 2, 8);
// draw the camera
ellipse(*pImg, selected_ellipses[(*(ite_cams+cams_index))[0]], Scalar(0, 255, 0), 2, 8);
ellipse(*pImg, selected_ellipses[(*(ite_cams+cams_index))[1]], Scalar(0, 255, 0), 2, 8);
imshow("show", *pImg);
// find the upper camera
int m1 = (*(ite_cams+cams_index))[0];
int m2 = (*(ite_cams+cams_index))[1];
int upper;
if(selected_ellipses[m1].center.y < selected_ellipses[m2].center.y)
upper = m1;
else
upper = m2;
*x = selected_ellipses[upper].center.x;
*y = selected_ellipses[upper].center.y;
return 1;
}
int main()
{
Mat imO = imread("Capture.PNG");
double x, y;
FindNao(&imO, &x, &y);
cout<<x<<" "<<y<<endl;
cvWaitKey(0);
}