OpenCV 计算物体的凸包

步骤

  1. 滤波——消除噪声
  2. 增强——二值化,使轮廓更明显
  3. 检测——选出边缘点
  4. 计算凸包

例程

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <opencv2/highgui/highgui_c.h>
#include <iostream>
#include <stdio.h>
#include <stdlib.h>

using namespace cv;
using namespace std;

Mat src; Mat src_gray;
int thresh = 100;
int max_thresh = 255;
RNG rng(12345);

/// Function header
void thresh_callback(int, void*);

/** @function main */
int main(int argc, char** argv)
{
	/// 加载源图像
	src = imread("../images/hands2.jpg");

	/// 转成灰度图并进行模糊降噪
	cvtColor(src, src_gray, CV_BGR2GRAY);
	blur(src_gray, src_gray, Size(3, 3));

	/// 创建窗体
	const char* source_window = "Source";
	namedWindow(source_window, CV_WINDOW_AUTOSIZE);
	imshow(source_window, src);

	createTrackbar(" Threshold:", "Source", &thresh, max_thresh, thresh_callback);
	thresh_callback(0, 0);

	waitKey(0);
	return(0);
}

/** @function thresh_callback */
void thresh_callback(int, void*)
{
	Mat src_copy = src.clone();
	Mat threshold_output;
	vector<vector<Point> > contours;
	vector<Vec4i> hierarchy;

	/// 对图像进行二值化
	threshold(src_gray, threshold_output, thresh, 255, THRESH_BINARY);

	/// 寻找轮廓
	findContours(threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));

	/// 对每个轮廓计算其凸包
	vector<vector<Point> >hull(contours.size());
	for (int i = 0; i < contours.size(); i++)
	{
		convexHull(Mat(contours[i]), hull[i], false);
	}

	/// 绘出轮廓及其凸包
	Mat drawing = Mat::zeros(threshold_output.size(), CV_8UC3);
	for (int i = 0; i < contours.size(); i++)
	{
		Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
		drawContours(drawing, contours, i, color, 1, 8, vector<Vec4i>(), 0, Point());
		drawContours(drawing, hull, i, color, 1, 8, vector<Vec4i>(), 0, Point());
	}

	/// 把结果显示在窗体
	namedWindow("Hull demo", CV_WINDOW_AUTOSIZE);
	imshow("Hull demo", drawing);
}

这个手实在是太花哨了,必须得把阈值调得很大
这张颜色就很单一,阈值相对低很多

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