الگوریتمش به صورت زیر
#include <opencv2/opencv.hpp>
#include <iostream>
using namespace std;
using namespace cv;
uchar maxentropie(const Mat1b& src, Mat1b& dst)
{
// Histogram
Mat1d hist(1, 256, 0.0);
for (int r=0; r<src.rows; ++r)
for (int c=0; c<src.cols; ++c)
hist(src(r,c))++;
// Normalize
hist /= double(src.rows * src.cols);
// Cumulative histogram
Mat1d cumhist(1, 256, 0.0);
float sum = 0;
for (int i = 0; i < 256; ++i)
{
sum += hist(i);
cumhist(i) = sum;
}
Mat1d hl(1, 256, 0.0);
Mat1d hh(1, 256, 0.0);
for (int t = 0; t < 256; ++t)
{
// low range entropy
double cl = cumhist(t);
if (cl > 0)
{
for (int i = 0; i <= t; ++i)
{
if (hist(i) > 0)
{
hl(t) = hl(t) - (hist(i) / cl) * log(hist(i) / cl);
}
}
}
// high range entropy
double ch = 1.0 - cl; // constraint cl + ch = 1
if (ch > 0)
{
for (int i = t+1; i < 256; ++i)
{
if (hist(i) > 0)
{
hh(t) = hh(t) - (hist(i) / ch) * log(hist(i) / ch);
}
}
}
}
// choose best threshold
Mat1d entropie(1, 256, 0.0);
double h_max = hl(0) + hh(0);
uchar threshold = 0;
entropie(0) = h_max;
for (int t = 1; t < 256; ++t)
{
entropie(t) = hl(t) + hh(t);
if (entropie(t) > h_max)
{
h_max = entropie(t);
threshold = uchar(t);
}
}
// Create output image
dst = src > threshold;
return threshold;
}
int main()
{
Mat1b img = imread("path_to_image", IMREAD_GRAYSCALE);
Mat1b res;
uchar th = maxentropie(img, res);
imshow("Original", img);
imshow("Result", res);
waitKey();
return 0;
}