void otsu() {

	char fname[10000];

	while (openFileDlg(fname))
	{

		Mat img = imread(fname, CV_LOAD_IMAGE_GRAYSCALE);
		imshow("original image", img);

		Mat dst = Mat::zeros(img.rows, img.cols, CV_8UC1);



		for (int i = 0; i < 256; i++)
		{
			histValues[i] = 0;
		}


		for (int i = 0; i < img.rows; i++)
		{
			for (int j = 0; j < img.cols; j++)
			{
				histValues[img.at<uchar>(i, j)]++;
			}
		}

		for (int i = 0; i < 256; i++)
		{
			histNorm[i] = (double)histValues[i] / 256;
		}

		showHistogram("MyHist", histValues, 256, 500);
		showHistogram("MyHistNormalized", histNorm, 256, 500);


		double miu = 0;
		double suma = 0, sumaB = 0;
		int N, threshold, q1 = 0, q2 = 0, miu1 = 0, miu2 = 0;
		N = img.rows * img.cols;

		double teta = 0, var_max = 0;


		for (int i = 0; i < 256; i++)
		{
			suma += i * histValues[i];
		}




		for (int t = 0; t < 256; t++)
		{
			q1 += histValues[t];

			if (q1 != 0)
			{
				q2 = N - q1;

				sumaB += t * histValues[t];

				miu1 = sumaB / q1;
				miu2 = (suma - sumaB) / q2;


				teta = q1 * q2 * (miu1 - miu2) * (miu1 - miu2);

				if (teta > var_max)
				{
					threshold = t;
					var_max = teta;
				}
			}

		}

		printf("Threshold = %d", threshold);

		for (int i = 0; i < img.rows; i++) {
			for (int j = 0; j < img.cols; j++)
			{
				if (img.at<uchar>(i, j) > threshold)
					dst.at<uchar>(i, j) = 255;
				else
					dst.at<uchar>(i, j) = 0;

			}
		}

		imshow("Otsu", dst);

	}

}