int MainWindow::generateKernel() {
// Fill List with options
QStringList items;
items << tr("Gauss") << tr("Kirsch (rotating)");
items << tr("Laplacian of the Gaussian (5x5)");
items << tr("Prewitt 1 (rotating)") << tr("Prewitt 2 (rotating)");
items << tr("Sobel (rotating)") << tr("other");
// ask user
bool ok;
QString item = QInputDialog::getItem(this, tr("QInputDialog::getItem()"),
tr("Season:"), items, 0, false, &ok);
if (!ok || item.isEmpty()){
return -1;
}
statusBar()->showMessage("choosen " + item);
// interpret data
switch(items.indexOf(item)) {
case 0: //Gauss
return kernelGauss();
break;
case 1: //Kirsch
return kernelKirsch();
break;
case 2: //Laplace
return kernelLaplace();
break;
case 3: //Prewitt 1
return kernelPrewitt1();
break;
case 4: //Prewitt 2
return kernelPrewitt2();
break;
case 5: //Sobel
return kernelSobel();
break;
case 6: //other
return kernelOther();
break;
default:
return -1;
}
return 0;
}
cv::Mat LoGFilter::process(cv::Mat &a_image) {
cv::Mat result;
// Allocate if necessary
result.create(a_image.size(), a_image.type());
// Constroi kernel Gauss; todas entradas = 1/16
cv::Mat kernelGauss(3, 3, CV_32F, cv::Scalar(0.0625));
// Define matriz do filtro de Gauss
kernelGauss.at<float>(0, 1) = 0.125;
kernelGauss.at<float>(1, 0) = 0.125;
kernelGauss.at<float>(1, 1) = 0.25;
kernelGauss.at<float>(1, 2) = 0.125;
kernelGauss.at<float>(2, 1) = 0.125;
// Convolve imagem original com filtro de Gauss
cv::filter2D(a_image, result, a_image.depth(), kernelGauss);
// Constroi kernel Laplace; todas entradas = 0
cv::Mat kernelLaplace(3, 3, CV_32F, cv::Scalar(0.0));
// Define matriz do filtro de Laplace
kernelLaplace.at<float>(0, 1) = -1.0;
kernelLaplace.at<float>(1, 0) = -1.0;
kernelLaplace.at<float>(1, 1) = +4.0;
kernelLaplace.at<float>(1, 2) = -1.0;
kernelLaplace.at<float>(2, 1) = -1.0;
/*
// versao negativa
float matrizLaplace [] = {
0f, 1f, 0f,
1f, -4f, 1f,
0f, 1f, 0f
};
*/
// Convolve imagem Gauss com filtro de Laplace
cv::filter2D(result, result, a_image.depth(), kernelLaplace);
return result;
}
