void MarkerDetector::recognizeMarkers(const cv::Mat& grayscale, std::vector<Marker>& detectedMarkers)
{
std::vector<Marker> goodMarkers;
// Identify the markers
for (size_t i=0;i<detectedMarkers.size();i++)
{
Marker& marker = detectedMarkers[i];
// Find the perspective transformation that brings current marker to rectangular form
cv::Mat markerTransform = cv::getPerspectiveTransform(marker.points, m_markerCorners2d);
// Transform image to get a canonical marker image
cv::warpPerspective(grayscale, canonicalMarkerImage, markerTransform, markerSize);
#ifdef SHOW_DEBUG_IMAGES
{
cv::Mat markerImage = grayscale.clone();
marker.drawContour(markerImage);
cv::Mat markerSubImage = markerImage(cv::boundingRect(marker.points));
cv::showAndSave("Source marker" + ToString(i), markerSubImage);
cv::showAndSave("Marker " + ToString(i) + " after warp", canonicalMarkerImage);
}
#endif
int nRotations;
int id = Marker::getMarkerId(canonicalMarkerImage, nRotations);
if (id !=- 1)
{
marker.id = id;
//sort the points so that they are always in the same order no matter the camera orientation
std::rotate(marker.points.begin(), marker.points.begin() + 4 - nRotations, marker.points.end());
goodMarkers.push_back(marker);
}
}
// Refine marker corners using sub pixel accuracy
if (goodMarkers.size() > 0)
{
std::vector<cv::Point2f> preciseCorners(4 * goodMarkers.size());
for (size_t i=0; i<goodMarkers.size(); i++)
{
const Marker& marker = goodMarkers[i];
for (int c = 0; c <4; c++)
{
preciseCorners[i*4 + c] = marker.points[c];
}
}
cv::TermCriteria termCriteria = cv::TermCriteria(cv::TermCriteria::MAX_ITER | cv::TermCriteria::EPS, 30, 0.01);
cv::cornerSubPix(grayscale, preciseCorners, cvSize(5,5), cvSize(-1,-1), termCriteria);
// Copy refined corners position back to markers
for (size_t i=0; i<goodMarkers.size(); i++)
{
Marker& marker = goodMarkers[i];
for (int c=0;c<4;c++)
{
marker.points[c] = preciseCorners[i*4 + c];
}
}
}
#if SHOW_DEBUG_IMAGES
{
cv::Mat markerCornersMat(grayscale.size(), grayscale.type());
markerCornersMat = cv::Scalar(0);
for (size_t i=0; i<goodMarkers.size(); i++)
{
goodMarkers[i].drawContour(markerCornersMat, cv::Scalar(255));
}
cv::showAndSave("Markers refined edges", grayscale * 0.5 + markerCornersMat);
}
#endif
detectedMarkers = goodMarkers;
}
// This function takes the input list of parallelepipeds and verifies wheter they are markers or not.
// The following are the main steps performed:
// 1. Removal of the perspective projection to obtain a frontal view of the rectangle area.
// 2. Perform a thresholding of the image using the Otsu algorithm (see: Marker::getMarkerId).
// 3. Identify the marker internal code: the marker is divided into a 7x7 grid.
// The internal 5x5 cells contain ID information, and the rest represent the external black border.
void MarkerDetector::detectMarkers(const cv::Mat& grayscale, std::vector<Marker>& detectedMarkers)
{
std::vector<Marker> goodMarkers;
// Identify the markers.
for (size_t i = 0; i < detectedMarkers.size(); i++) {
Marker& marker = detectedMarkers[i];
// To get the rectangle marker image we have to unwarp the input image using the proper perspective transformation.
// This matrix can be retrieved from pairs of corresponding points (marker coords in image space + square marker image coords).
// Find the perspective transformation that brings current marker to rectangular form.
// See: http://docs.opencv.org/modules/imgproc/doc/geometric_transformations.html#getperspectivetransform
cv::Mat markerTransform = cv::getPerspectiveTransform(marker.points, markerCorners2D);
// Transform image to get a canonical marker image.
// See: http://docs.opencv.org/modules/imgproc/doc/geometric_transformations.html#warpperspective
cv::warpPerspective(grayscale, canonicalMarkerImage, markerTransform, markerSize);
#ifdef _DEBUG
cv::Mat markerImage = grayscale.clone();
marker.drawContour(markerImage);
cv::Mat markerSubImage = markerImage(cv::boundingRect(marker.points));
cv::imshow("Source Marker", markerSubImage);
cv::imshow("Marker After Warp", canonicalMarkerImage);
#endif
int nRotations;
int id = Marker::getMarkerId(canonicalMarkerImage, nRotations);
if (id != -1) {
// After finding the right marker orientation,
// we rotate the corners of the marker respectively to conform to their order.
marker.id = id;
// Sort the points so that they are always in the same order no matter the camera orientation.
std::rotate(marker.points.begin(), marker.points.begin() + 4 - nRotations, marker.points.end());
goodMarkers.push_back(marker);
}
}
// Refine marker corners using sub pixel accuracy.
if (goodMarkers.size() > 0) {
// After detecting a marker and decoding its ID, we will refine its corners.
// This operation will ease the next step consisting in the estimation of the marker 3D position.
// To find the corner location with subpixel accuracy we use the cv::cornerSubPix function:
// 1. prepare the input data copying the list of vertices,
// 2. then we call cv::cornerSubPix with the proper input arguments,
// 3. finally we copy the refined locations back to marker corners.
// * We do not use cv::cornerSubPix in the earlier stages of marker detection due to its complexity.
// It is very computationally expensive to call this function for large numbers of points.
// Therefore we do this only for valid markers.
std::vector<cv::Point2f> preciseCorners(4 * goodMarkers.size());
for (size_t i = 0; i < goodMarkers.size(); i++) {
const Marker& marker = goodMarkers[i];
for (int c = 0; c < 4; c++) { preciseCorners[i * 4 + c] = marker.points[c]; }
}
cv::TermCriteria termCriteria = cv::TermCriteria(cv::TermCriteria::MAX_ITER | cv::TermCriteria::EPS, 30, 0.01);
cv::cornerSubPix(grayscale, preciseCorners, cv::Size(5, 5), cv::Size(-1, -1), termCriteria);
// Copy refined corners position back to markers.
for (size_t i = 0; i < goodMarkers.size(); i++) {
Marker& marker = goodMarkers[i];
for (int c = 0; c < 4; c++) { marker.points[c] = preciseCorners[i * 4 + c]; }
}
}
#ifdef _DEBUG
cv::Mat markerCornersMat(grayscale.size(), grayscale.type());
markerCornersMat = cv::Scalar(0);
for (size_t i = 0; i < goodMarkers.size(); i++) { goodMarkers[i].drawContour(markerCornersMat, cv::Scalar(255)); }
cv::imshow("Markers Refined Edges", grayscale * 0.5 + markerCornersMat);
#endif
detectedMarkers = goodMarkers;
}
