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#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("circles.jpg"); if (!srcImage.data) return 0; cv::Mat grayImage; cv::cvtColor(srcImage, grayImage, cv::COLOR_BGR2GRAY); cv::Mat result = maxEntropySegMentation(grayImage); cv::imshow("grayImage", grayImage); cv::imshow("result", result); cv::waitKey(0); return 0; }
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