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[OpenCV] Samples 05: convexhull
得到了复杂轮廓往往不适合特征的检测，这里再介绍一个点集凸包络的提取函数convexHull，输入参数就可以是contours组中的一个轮廓，返回外凸包络的点集 ---- 如此就能去掉凹进去的边。
对于凸包算法，其中最有名的莫过于Graham扫描算法，它的复杂度为nlog(n)
参考：计算几何之凸包（Algorithm show）, 寻找轮廓
高级：Snake模型在轮廓提取中的应用 cvSnakeImage()
#include "opencv2/imgproc/imgproc.hpp"#include "opencv2/highgui/highgui.hpp"#include <fstream>#include <iostream>using namespace cv;using namespace std;static void help(){ cout << "\nThis sample program demonstrates the use of the convexHull() function\n" << "Call:\n" << "./convexhull\n" << endl;}int main( int argc, char** argv ){ CommandLineParser parser(argc, argv, "{help h||}"); if (parser.has("help")) { help(); return 0; } Mat img(500, 500, CV_8UC3); RNG& rng = theRNG(); for(;;) { char key; int i, count = (unsigned)rng%100 + 1; vector<Point> points; for( i = 0; i < count; i++ ) { Point pt; pt.x = rng.uniform(img.cols/4, img.cols*3/4); pt.y = rng.uniform(img.rows/4, img.rows*3/4); points.push_back(pt); } // Jeff --> hull is the indice of corner points vector<int> hull; convexHull(Mat(points), hull, true);/******************************************************************************/ // Jeff --> draw the effect. img = Scalar::all(0); for( i = 0; i < count; i++ ) circle(img, points[i], 3, Scalar(0, 0, 255), FILLED, LINE_AA); int hullcount = (int)hull.size(); cout << hullcount << endl; Point pt0 = points[hull[hullcount-1]]; for( i = 0; i < hullcount; i++ ) { // Jeff --> extract corners. Point pt = points[hull[i]]; line(img, pt0, pt, Scalar(0, 255, 0), 1,LINE_AA); pt0 = pt; } imshow("hull", img); key = (char)waitKey(); if( key == 27 || key == ‘q‘ || key == ‘Q‘ ) // ‘ESC‘ break; } return 0;}
轮廓的进一步描述
进一步参见：OpenCV成长之路：直线、轮廓的提取与描述
[OpenCV] Samples 05: convexhull
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