Initial commit of the CoMoNoD algorithm with example file

#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;

	}

}