template<typename PointInT, typename PointOutT> void
pcl_1_8::Edge<PointInT, PointOutT>::detectEdgeCanny (pcl::PointCloud<PointOutT> &output)
{
float tHigh = hysteresis_threshold_high_;
float tLow = hysteresis_threshold_low_;
const int height = input_->height;
const int width = input_->width;
output.resize (height * width);
output.height = height;
output.width = width;
//pcl::console::TicToc tt;
//tt.tic ();
// Noise reduction using gaussian blurring
pcl::PointCloud<pcl::PointXYZI>::Ptr gaussian_kernel (new pcl::PointCloud<pcl::PointXYZI>);
PointCloudInPtr smoothed_cloud (new PointCloudIn);
kernel_.setKernelSize (3);
kernel_.setKernelSigma (1.0);
kernel_.setKernelType (kernel<pcl::PointXYZI>::GAUSSIAN);
kernel_.fetchKernel (*gaussian_kernel);
convolution_.setKernel (*gaussian_kernel);
convolution_.setInputCloud (input_);
convolution_.filter (*smoothed_cloud);
//PCL_ERROR ("Gaussian blur: %g\n", tt.toc ()); tt.tic ();
// Edge detection usign Sobel
pcl::PointCloud<PointXYZIEdge>::Ptr edges (new pcl::PointCloud<PointXYZIEdge>);
setInputCloud (smoothed_cloud);
detectEdgeSobel (*edges);
//PCL_ERROR ("Sobel: %g\n", tt.toc ()); tt.tic ();
// Edge discretization
discretizeAngles (*edges);
//PCL_ERROR ("Discretize: %g\n", tt.toc ()); tt.tic ();
// tHigh and non-maximal supression
pcl::PointCloud<pcl::PointXYZI>::Ptr maxima (new pcl::PointCloud<pcl::PointXYZI>);
suppressNonMaxima (*edges, *maxima, tLow);
//PCL_ERROR ("NM suppress: %g\n", tt.toc ()); tt.tic ();
// Edge tracing
for (int i = 0; i < height; i++)
{
for (int j = 0; j < width; j++)
{
if ((*maxima)(j, i).intensity < tHigh || (*maxima)(j, i).intensity == std::numeric_limits<float>::max ())
continue;
(*maxima)(j, i).intensity = std::numeric_limits<float>::max ();
cannyTraceEdge ( 1, 0, i, j, *maxima);
cannyTraceEdge (-1, 0, i, j, *maxima);
cannyTraceEdge ( 1, 1, i, j, *maxima);
cannyTraceEdge (-1, -1, i, j, *maxima);
cannyTraceEdge ( 0, -1, i, j, *maxima);
cannyTraceEdge ( 0, 1, i, j, *maxima);
cannyTraceEdge (-1, 1, i, j, *maxima);
cannyTraceEdge ( 1, -1, i, j, *maxima);
}
}
//PCL_ERROR ("Edge tracing: %g\n", tt.toc ());
// Final thresholding
for (size_t i = 0; i < input_->size (); ++i)
{
if ((*maxima)[i].intensity == std::numeric_limits<float>::max ())
output[i].magnitude = 255;
else
output[i].magnitude = 0;
}
}
template <typename PointInT, typename PointOutT> void
pcl_1_8::Edge<PointInT, PointOutT>::canny (
const pcl::PointCloud<PointInT> &input_x,
const pcl::PointCloud<PointInT> &input_y,
pcl::PointCloud<PointOutT> &output)
{
float tHigh = hysteresis_threshold_high_;
float tLow = hysteresis_threshold_low_;
const int height = input_x.height;
const int width = input_x.width;
output.resize (height * width);
output.height = height;
output.width = width;
// Noise reduction using gaussian blurring
pcl::PointCloud<pcl::PointXYZI>::Ptr gaussian_kernel (new pcl::PointCloud<pcl::PointXYZI>);
kernel_.setKernelSize (3);
kernel_.setKernelSigma (1.0);
kernel_.setKernelType (kernel<pcl::PointXYZI>::GAUSSIAN);
kernel_.fetchKernel (*gaussian_kernel);
convolution_.setKernel (*gaussian_kernel);
PointCloudIn smoothed_cloud_x;
convolution_.setInputCloud (input_x.makeShared());
convolution_.filter (smoothed_cloud_x);
PointCloudIn smoothed_cloud_y;
convolution_.setInputCloud (input_y.makeShared());
convolution_.filter (smoothed_cloud_y);
// Edge detection usign Sobel
pcl::PointCloud<PointXYZIEdge>::Ptr edges (new pcl::PointCloud<PointXYZIEdge>);
sobelMagnitudeDirection (smoothed_cloud_x, smoothed_cloud_y, *edges.get ());
// Edge discretization
discretizeAngles (*edges);
pcl::PointCloud<pcl::PointXYZI>::Ptr maxima (new pcl::PointCloud<pcl::PointXYZI>);
suppressNonMaxima (*edges, *maxima, tLow);
// Edge tracing
for (int i = 0; i < height; i++)
{
for (int j = 0; j < width; j++)
{
if ((*maxima)(j, i).intensity < tHigh || (*maxima)(j, i).intensity == std::numeric_limits<float>::max ())
continue;
(*maxima)(j, i).intensity = std::numeric_limits<float>::max ();
cannyTraceEdge ( 1, 0, i, j, *maxima);
cannyTraceEdge (-1, 0, i, j, *maxima);
cannyTraceEdge ( 1, 1, i, j, *maxima);
cannyTraceEdge (-1, -1, i, j, *maxima);
cannyTraceEdge ( 0, -1, i, j, *maxima);
cannyTraceEdge ( 0, 1, i, j, *maxima);
cannyTraceEdge (-1, 1, i, j, *maxima);
cannyTraceEdge ( 1, -1, i, j, *maxima);
}
}
// Final thresholding
for (int i = 0; i < height; i++)
{
for (int j = 0; j < width; j++)
{
if ((*maxima)(j, i).intensity == std::numeric_limits<float>::max ())
output (j, i).magnitude = 255;
else
output (j, i).magnitude = 0;
}
}
}
int main(int argc, char **argv)
{
// Process command line
if (argc < 3)
Usage(argc, argv);
std::string inputFilename = argv[1];
std::string outputFilename = argv[2];
for (int i = 3; i < argc - 1; i += 2)
{
if (std::string(argv[i]) == std::string("-q"))
QLim = atof(argv[i+1]);
else if (std::string(argv[i]) == std::string("-w"))
WLimF = atof(argv[i+1]);
else if (std::string(argv[i]) == std::string("-f"))
FilterSize = atoi(argv[i+1]);
else if (std::string(argv[i]) == std::string("-m"))
NonMaximaBoxSize = atoi(argv[i+1]);
}
// Load image
image = new Ga::Image(inputFilename);
// Calculate tensor
Gu = new float[image->sizeX() * image->sizeY()];
Gv = new float[image->sizeX() * image->sizeY()];
Guv = new float[image->sizeX() * image->sizeY()];
computeStructureTensor(Gu, Gv, Guv);
// Apply boxfilter
computeBoxFilter(Gu, FilterSize);
computeBoxFilter(Gv, FilterSize);
computeBoxFilter(Guv, FilterSize);
// Calculate interest values
result = new Ga::Image(typeid(float), image->sizeX(), image->sizeY());
double wmean = 0;
double normalization = 0;
for (int y = 0; y < result->sizeY(); y++)
{
for (int x = 0; x < result->sizeX(); x++)
{
int index = y * image->sizeX() + x;
float trace = Gu[index] + Gv[index];
float determinant = (Gu[index] * Gv[index]) - (Guv[index] * Guv[index]);
float w = determinant / trace;
float q = (4 * determinant) / (trace * trace);
// Test for qlim and calculate wlim
if (q > QLim)
{
result->setPixel(x, y, w);
wmean += w;
normalization++;
}
else
result->setPixel(x, y, 0);
}
}
WLim = (wmean / normalization) * WLimF;
for (int y = 0; y < result->sizeY(); y++)
{
for (int x = 0; x < result->sizeX(); x++)
{
int index = y * image->sizeX() + x;
float trace = Gu[index] + Gv[index];
float determinant = (Gu[index] * Gv[index]) - (Guv[index] * Guv[index]);
float w = determinant / trace;
// Test for wlim
if (w <= WLim)
result->setPixel(x, y, 0);
}
}
// Suppress local non-maxima
suppressNonMaxima(NonMaximaBoxSize);
// Write result image
result->write(outputFilename.c_str());
// Release memory
delete image;
delete result;
delete[] Gu;
delete[] Gv;
delete[] Guv;
// Return
return 0;
}
