void ColorSeparation(const Mat targetImg, vector<StrokeCluster> &fisrtDrawCluster){
// Mean shifting
Mat colorSegment = Mat(targetImg.size(), CV_8UC3, Scalar(255, 255, 255));
IplImage* img = cvCloneImage(&(IplImage)targetImg);
int **ilabels = new int *[img->height];
for (int i = 0; i < img->height; i++) ilabels[i] = new int[img->width];
int regionNum = MeanShift(img, ilabels);
cout << "Segment region number: " << regionNum << endl;
vector <vector<Point>> fillRegionPoints;
vector <Mat> fillRegions;
vector<Scalar> colorValue;
// Initial
for (int i = 0; i < regionNum; i++){
colorValue.push_back(Scalar(0, 0, 0));
fillRegions.push_back(Mat(targetImg.size(), CV_8UC3, Scalar(255, 255, 255)));
}
fillRegionPoints.resize(regionNum);
// Sort blobs size
for (int i = 0; i < targetImg.rows; i++)
for (int j = 0; j < targetImg.cols; j++)
{
int label = ilabels[i][j];
fillRegionPoints[label].push_back(Point(i, j));
}
sort(fillRegionPoints.begin(), fillRegionPoints.end(), CompareLength);
// Compute average color
for (int i = 0; i < fillRegionPoints.size(); i++){
int pixNum = fillRegionPoints[i].size();
for (int j = 0; j < fillRegionPoints[i].size(); j++)
{
int x = fillRegionPoints[i][j].x;
int y = fillRegionPoints[i][j].y;
colorValue[i] += Scalar(targetImg.at<Vec3b>(x, y)[0], targetImg.at<Vec3b>(x, y)[1], targetImg.at<Vec3b>(x, y)[2])/pixNum;
}
}
// Recover origin average color
for (int i = 0; i < fillRegionPoints.size(); i++){
Scalar color = colorValue[i];
for (int j = 0; j < fillRegionPoints[i].size(); j++){
int x = fillRegionPoints[i][j].x;
int y = fillRegionPoints[i][j].y;
colorSegment.at<Vec3b>(x, y) = Vec3b(color[0], color[1], color[2]);
fillRegions[i].at<Vec3b>(x, y) = Vec3b(color[0], color[1], color[2]);
}
}
// Background Removal
colorValue.erase(colorValue.begin());
fillRegions.erase(fillRegions.begin());
ShowImg("Color Segment", colorSegment,-1);
imwrite("Color Segment.jpg", colorSegment);
fisrtDrawCluster.resize(fillRegions.size());
FillSimulation(fillRegions, colorValue, fisrtDrawCluster);
}
void MeanShiftTracker::trackObject(const cv::Mat &image) {
double temp = 0;
double pu_actual[colorBins][colorBins][colorBins];
double pu_nuevo[colorBins][colorBins][colorBins];
cv::Point newCenter = cv::Point(-1, -1);
cv::Point currentCenter = cv::Point(-1, -1);
currentCenter = trackingWindowCenter;
iteration = 1;
do
{
getPu(image, pu_actual, currentCenter);
newCenter = MeanShift(image, pu_actual, currentCenter);
getPu(image, pu_nuevo, newCenter);
temp = getBhattaCoefficient(qu, pu_nuevo) - getBhattaCoefficient(qu, pu_actual) ;
if (temp < bhattaEpsilon || (iteration == maxIterations))
{
if (temp < 0)
newCenter = currentCenter;
bhattaCoefficient = getBhattaCoefficient(qu, pu_nuevo);
break;
}
else
{
currentCenter = newCenter;
iteration += 1;
}
}
while (true);
getPu(image, pu_nuevo, newCenter);
double newPu = getBhattaCoefficient(qu, pu_nuevo);
lastError = newPu;
trackingWindowCenter = newCenter;
if (enableModelUpdate)
//if (getBhattaCoefficient(qu, pu_nuevo) < modelUpdateEpsilon)
updateModel(image, newCenter);
trackingWindow = calculateTrackingWindow(trackingWindowCenter);
}
