Commit 102b7a76 authored by Timm Schoening's avatar Timm Schoening

Initial commit of the CoMoNoD algorithm with example file

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#include "comonod.hpp"
using namespace std;
int main() {
// Load input image
cv::Mat img = cv::imread("/media/tschoening/files/data/nodule_datasets/JC120_NOCS_AutoSub/images/Picture_42.jpg");
// CoMoNoD input parameter that governs the selection of the adaptive threshold
float theta_gamma = 0.08;
// CoMoNoD input parameter representing the minimum nodule size in px
uint theta_r = 5;
// The median area of all images in the data set (in m^2)
float median_area = 1.745380165;
// The area of the image to be processed (in m^2)
float image_area = 1.983397784;
// The top left and bottom right pixel coordinates of the region of interest to process with CoMoNoD
cv::Point top_left(100,100);
cv::Point bottom_right(img.cols-100,img.rows-100);
// Execute the contrast maximization, nodule delineation and nodule statistic computation
vector<double> phis;
// Run CoMoNoD and filter for nodules larger than 3.14cm^2 size
if(ocv::runCoMoNoD(img,theta_gamma, theta_r, median_area, image_area, top_left, bottom_right, phis, 3.14)) {
// NOTE: Phis contains descriptive nodule statistics for the image.
// NOTE: Further analysis would follow here.
// Dump the phis
for(double phi : phis)
cout << phi << " ";
cout << endl;
// Compute and dump the Trask particle size metrics
for(double val : ocv::particleSizeAnalysis({phis[2],phis[3],phis[4]}))
cout << val << " ";
cout << endl;
}
}
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