多边形压缩Douglas-Peucker算法，上代码！
#include <iostream>
#include <cmath>
#include <utility>
#include <vector>
#include <stdexcept>
#include <opencv2/opencv.hpp> // 包含OpenCV头文件using namespace std;typedef std::pair<double, double> Point;//使用向量发计算高度
double PerpendicularDistance(const Point& pt, const Point& lineStart, const Point& lineEnd)
{double dx = lineEnd.first - lineStart.first;double dy = lineEnd.second - lineStart.second;//Normalizedouble mag = pow(pow(dx, 2.0) + pow(dy, 2.0), 0.5);if (mag > 0.0){dx /= mag; dy /= mag;}double pvx = pt.first - lineStart.first;double pvy = pt.second - lineStart.second;//Get dot product (project pv onto normalized direction)double pvdot = dx * pvx + dy * pvy;//Scale line direction vectordouble dsx = pvdot * dx;double dsy = pvdot * dy;//Subtract this from pvdouble ax = pvx - dsx;double ay = pvy - dsy;return pow(pow(ax, 2.0) + pow(ay, 2.0), 0.5);
}//递归逐一计算
void RamerDouglasPeucker(const vector<Point>& pointList, double epsilon, vector<Point>& out)
{if (pointList.size() < 2)throw invalid_argument("Not enough points to simplify");// Find the point with the maximum distance from line between start and enddouble dmax = 0.0;size_t index = 0;size_t end = pointList.size() - 1;for (size_t i = 1; i < end; i++){double d = PerpendicularDistance(pointList[i], pointList[0], pointList[end]);if (d > dmax){index = i;dmax = d;}}// If max distance is greater than epsilon, recursively simplifyif (dmax > epsilon){// Recursive callvector<Point> recResults1;vector<Point> recResults2;vector<Point> firstLine(pointList.begin(), pointList.begin() + index + 1);vector<Point> lastLine(pointList.begin() + index, pointList.end());RamerDouglasPeucker(firstLine, epsilon, recResults1);RamerDouglasPeucker(lastLine, epsilon, recResults2);// Build the result listout.assign(recResults1.begin(), recResults1.end() - 1);out.insert(out.end(), recResults2.begin(), recResults2.end());if (out.size() < 2)throw runtime_error("Problem assembling output");}else{//Just return start and end pointsout.clear();out.push_back(pointList[0]);out.push_back(pointList[end]);}
}int main()
{vector<Point> pointList;vector<Point> pointListOut;pointList.push_back(Point(0.0, 6.0));pointList.push_back(Point(1.0, 1.1));pointList.push_back(Point(3.0, 5.0));pointList.push_back(Point(4.0, 6.0));pointList.push_back(Point(5.0, 7.0));pointList.push_back(Point(6.0, 8.1));pointList.push_back(Point(7.0, 9.0));pointList.push_back(Point(8.0, 9.0));pointList.push_back(Point(9.0, 9.0));pointList.push_back(Point(2.0, 10.2));cv::Mat canvas(200, 200, CV_8UC3, cv::Scalar(255, 255, 255)); // 创建一个300x300像素的画布// 显示第一个圆for (auto i : pointList) {cv::circle(canvas, cv::Point(i.first*10, i.second*10), 2, cv::Scalar(0, 0, 255), -1);cv::imshow("Canvas", canvas);cv::waitKey(300); // 等待10秒}cv::waitKey(900);RamerDouglasPeucker(pointList, 1.0, pointListOut);cout << "result" << endl;for (size_t i = 0; i < pointListOut.size(); i++){cv::circle(canvas, cv::Point(pointListOut[i].first * 10, pointListOut[i].second * 10), 2, cv::Scalar(255, 0, 0), -1);cv::imshow("Canvas", canvas);cv::waitKey(300); // 等待10秒cout << pointListOut[i].first << "," << pointListOut[i].second << endl;}system("pause");return 0;
}
进程的核心—task_truct)
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