/*************************************************************************
* @函数名称：
* calGradSim()
* @输入:
* const IplImage* image1 - 输入图像1
* const IplImage* image2 - 输入图像2
* @返回值:
* double g - 梯度相似性
* @说明:
* 计算图像梯度相似性
*************************************************************************/
double calGradSim(const IplImage* image1, const IplImage* image2)
{
double c4 = 0;
double g = 0;
IplImage* g1;
IplImage* g2;
IplImage* tmp;
g1=gradientImage(image1);
g2=gradientImage(image2);
tmp = cvCloneImage(g1);
cvMul(g1, g2, tmp);
cvMul(g1, g1, g1);
cvMul(g2, g2, g2);
CvScalar s1 = cvSum(tmp);
CvScalar s2 = cvSum(g1);
CvScalar s3 = cvSum(g2);
c4 = (0.03 * 255) * (0.03 * 255);
g = (2 * s1.val[0] + c4) / (s2.val[0] +s3.val[0] + c4);
cvReleaseImage(&g1);
cvReleaseImage(&g2);
cvReleaseImage(&tmp);
return g;
}
void FeatureEval::sobel_erode(){
boost::shared_ptr<PointCloud> cloud = core_->cl_->active_;
if(cloud == nullptr)
return;
int h = cloud->scan_width();
int w = cloud->scan_height();
// Create distance map
boost::shared_ptr<std::vector<float>> distmap = makeDistmap(cloud);
boost::shared_ptr<std::vector<float> > grad_image = gradientImage(distmap, w, h);
boost::shared_ptr<std::vector<float> > smooth_grad_image = convolve(grad_image, w, h, gaussian, 5);
// Threshold && Erode
const int strct[] = {
0, 1, 0,
1, 0, 1,
0, 1, 0,
};
boost::shared_ptr<std::vector<float> > dilated_image = morphology(
smooth_grad_image,
w, h, strct, 3, Morphology::ERODE,
grad_image); // <-- reuse
drawFloats(dilated_image, cloud);
}
int main( int argc, char** argv )
{
osg::ArgumentParser arguments( &argc, argv );
osg::ref_ptr<osg::MatrixTransform> scene = new osg::MatrixTransform;
scene->addChild( createImageQuad(gradientImage(), osg::Vec3()) );
scene->addChild( createImageQuad(textImage(), osg::Vec3(1.1f, 0.0f, 0.0f)) );
osgViewer::Viewer viewer;
viewer.addEventHandler( new osgGA::StateSetManipulator(viewer.getCamera()->getOrCreateStateSet()) );
viewer.addEventHandler( new osgViewer::StatsHandler );
viewer.addEventHandler( new osgViewer::WindowSizeHandler );
viewer.setSceneData( scene.get() );
return viewer.run();
}
void FeatureEval::sobel_blur(){
boost::shared_ptr<PointCloud> cloud = core_->cl_->active_;
if(cloud == nullptr)
return;
int h = cloud->scan_width();
int w = cloud->scan_height();
// Create distance map
boost::shared_ptr<std::vector<float>> distmap = makeDistmap(cloud);
boost::shared_ptr<std::vector<float> > smooth_grad_image = gradientImage(distmap, w, h);
int blurs = 0;
for(int i = 0; i < blurs; i++)
smooth_grad_image = convolve(smooth_grad_image, w, h, gaussian, 5);
drawFloats(smooth_grad_image, cloud);
}
