#include <iostream>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace std;
using namespace cv;
float caculateCurrentEntropy(cv::Mat hist, int threshold) {
float BackgroundSum = 0, targetSum = 0;
const float *pDataHist = (float *)hist.ptr<float>(0);
for (int i = 0; i < 256; i++) {
if (i < threshold) {
BackgroundSum += pDataHist[ i ];
} else
{
targetSum += pDataHist[ i ];
}
}
float BackgroundEntropy = 0, targetEntropy = 0;
for (int i = 0; i < 256; i++) {
if (i < threshold) {
if (pDataHist[ i ] == 0)
continue;
float ratio1 = pDataHist[ i ] / BackgroundSum;
BackgroundEntropy += -ratio1 * logf(ratio1);
} else
{
if (pDataHist[ i ] == 0)
continue;
float ratio2 = pDataHist[ i ] / targetSum;
targetEntropy += -ratio2 * logf(ratio2);
}
}
return (targetEntropy + BackgroundEntropy);
}
cv::Mat maxEntropySegMentation(cv::Mat inputImage) {
const int channels[ 1 ] = {0};
const int histSize[ 1 ] = {256};
float pranges[ 2 ] = {0, 256};
const float *ranges[ 1 ] = {pranges};
cv::MatND hist;
cv::calcHist(&inputImage, 1, channels, cv::Mat(), hist, 1, histSize, ranges);
float maxentropy = 0;
int max_index = 0;
cv::Mat result;
for (int i = 0; i < 256; i++) {
float cur_entropy = caculateCurrentEntropy(hist, i);
if (cur_entropy > maxentropy) {
maxentropy = cur_entropy;
max_index = i;
}
}
threshold(inputImage, result, max_index, 255, CV_THRESH_BINARY);
return result;
}
int main() {
cv::Mat srcImage = cv::imread("..\\images\\hand1.jpg");
if (!srcImage.data)
return 0;
cv::Mat grayImage;
cv::cvtColor(srcImage, grayImage, CV_BGR2GRAY);
cv::Mat result = maxEntropySegMentation(grayImage);
cv::imshow("grayImage", grayImage);
cv::imshow("result", result);
cv::waitKey(0);
return 0;
}