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101 lines
3.7 KiB
C++
101 lines
3.7 KiB
C++
2 months ago
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#include "image_utilities.h"
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#include <opencv2/imgproc.hpp>
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#include <vector>
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#include <cmath>
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#include <iostream>
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#include <exception>
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using namespace std;
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vector<cv::Point> mrect2box(const cv::RotatedRect& mrect) {
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cv::Point2f boxPoints[4];
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mrect.points(boxPoints);
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vector<cv::Point> result;
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for (int i = 0; i < 4; ++i) {
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result.emplace_back(cv::Point(static_cast<int>(boxPoints[i].x), static_cast<int>(boxPoints[i].y)));
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}
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return result;
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}
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cv::Mat block_threshold(const cv::Mat& gray) {
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try {
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int height = gray.rows;
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int width = gray.cols;
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vector<int> divisions = {8, 13};
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vector<int> block_sizes;
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for (int div : divisions) {
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int size = max(19, (height + width) / 2 / div);
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if (size % 2 == 0) size++;
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block_sizes.push_back(size);
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}
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vector<pair<int, int>> block_strategies;
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for (int size : block_sizes) {
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block_strategies.push_back({size, 0});
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block_strategies.push_back({size, size / 2});
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}
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cv::Mat otsu;
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double global_threshold = cv::threshold(gray, otsu, 0, 255, cv::THRESH_BINARY_INV | cv::THRESH_OTSU);
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cv::Mat adaptive_ref;
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cv::adaptiveThreshold(gray, adaptive_ref, 255, cv::ADAPTIVE_THRESH_GAUSSIAN_C, cv::THRESH_BINARY_INV, block_sizes[0], 20);
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cv::Mat result = cv::Mat::zeros(gray.size(), CV_8UC1);
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for (auto& strategy : block_strategies) {
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int block_size = strategy.first;
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int offset = strategy.second;
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cv::Mat current_result = cv::Mat::zeros(gray.size(), CV_8UC1);
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for (int y = offset; y < height; y += block_size) {
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for (int x = offset; x < width; x += block_size) {
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int end_y = min(y + block_size, height);
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int end_x = min(x + block_size, width);
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cv::Mat block_roi = gray(cv::Rect(x, y, end_x - x, end_y - y));
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cv::Scalar mean, stddev;
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cv::meanStdDev(block_roi, mean, stddev);
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double variance = stddev[0] * stddev[0];
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cv::Mat block_result;
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if (variance < 80) {
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block_result = cv::Mat::zeros(block_roi.size(), CV_8UC1);
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if (mean[0] < global_threshold) {
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block_result = cv::Mat::ones(block_roi.size(), CV_8UC1) * 255;
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}
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} else {
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cv::threshold(block_roi, block_result, 0, 255, cv::THRESH_BINARY_INV | cv::THRESH_OTSU);
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cv::Scalar ref_mean, block_mean;
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cv::Mat adaptive_block = adaptive_ref(cv::Rect(x, y, end_x - x, end_y - y));
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cv::meanStdDev(adaptive_block, ref_mean, cv::noArray());
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cv::meanStdDev(block_result, block_mean, cv::noArray());
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if (abs(ref_mean[0] - block_mean[0]) > 200) {
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block_result = 255 - block_result;
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}
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}
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block_result.copyTo(current_result(cv::Rect(x, y, end_x - x, end_y - y)));
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}
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}
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cv::bitwise_or(result, current_result, result);
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}
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return result;
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} catch (const exception& e) {
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cout << "Exception in block_threshold: " << e.what() << endl;
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return cv::Mat();
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} catch (...) {
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cout << "Unknown exception in block_threshold" << endl;
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return cv::Mat();
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}
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}
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