Initial commit of the CoMoNoD algorithm with example file

example.cpp

+#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;
+		
+	}
+
+}