opencv 实战，钢板焊接点寻找3

第三张图：
方法：轮廓检测后亚像素级角点检测，得出角点坐标，再提取
个人感觉这种方法抗干扰能力最好。
代码：
//第三张，轮廓检测后亚像素级角点检测 ，得出角点坐标

#include <opencv2/opencv.hpp>
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <cstdlib>
using namespace cv;
using namespace std;

#define WINDOW_NAME "【亚像素级角点检测】"        

Mat g_srcImage, g_grayImage;
int g_maxCornerNumber = 20;                             //点数初始值
int g_maxTrackbarNumber = 500;                          //点数上线
														//RNG g_rng(12345);                                      //初始化随机数生成器


void on_GoodFeaturesToTrack(int, void*)                //响应滑动条移动的回调函数
{
	if (g_maxCornerNumber <= 7) { g_maxCornerNumber = 7; }                      //对变量小于等于1时的处理

	vector<Point2f> corners;                                                    //Shi-Tomasi算法（goodFeaturesToTrack函数）的参数准备
	double qualityLevel = 0.01;                                                 //角点检测可接受的最小特征值
	double minDistance = 10;                                                    //角点之间的最小距离
	int blockSize = 3;                                                          //计算导数自相关矩阵时指定的邻域范围
	double k = 0.04;                                                            //权重系数

	Mat copy = g_srcImage.clone();

	//进行Shi-Tomasi角点检测
	goodFeaturesToTrack
	(g_grayImage,               //输入图像
		corners,                                   //检测到的角点的输出向量
		g_maxCornerNumber,                         //角点的最大数量
		qualityLevel,                              //角点检测可接受的最小特征值
		minDistance,                               //角点之间的最小距离
		Mat(),                                     //感兴趣区域
		blockSize,                                  //计算导数自相关矩阵时指定的邻域范围
		false,                                      //不使用Harris角点检测
		k);                                         //权重系数

	cout << "\n\t>-此次检测到的角点数量为：" << corners.size() << endl;

	//亚像素角点检测的参数设置
	Size winSize = Size(5, 5);
	Size zeroZone = Size(-1, -1);
	TermCriteria criteria = TermCriteria(TermCriteria::EPS + TermCriteria::MAX_ITER, 40, 0.001);

	//计算出亚像素角点位置
	cornerSubPix(g_grayImage, corners, winSize, zeroZone, criteria);
	Point2f lowstpoint, nextpoint, uppoint, mid;                         //初始化最下方点，下一个点，最下方上面的点,中间点
	lowstpoint = corners[0];
	uppoint = corners[0];

	for (int i = 0; i < corners.size(); i++)                                  //找出最低点
	{
		nextpoint = corners[i];
		if (nextpoint.y > lowstpoint.y) { lowstpoint = nextpoint; }

		if (i == corners.size() - 1)
		{
			for (int j = 0; j < corners.size(); j++)                          //已找到最后一个点，开始找竖直方向最近点
			{
				nextpoint = corners[j];
				float a = abs(nextpoint.x - lowstpoint.x);
				float b = abs(uppoint.x - lowstpoint.x);

				if (nextpoint != lowstpoint)                                  //除去最下方的点
				{
					if (a < b) { uppoint = nextpoint; }
				}

				if (j == corners.size() - 1)                                  //已找到竖直方向最近点，得到中间点
				{
					mid.x = (uppoint.x + lowstpoint.x) / 2;
					mid.y = (uppoint.y + lowstpoint.y) / 2;
					circle(copy, mid, 3, Scalar(0, 255, 0), -1, 8, 0);
					cout << " \t>>中间点坐标" << " (" << mid.x << "," << mid.y << ")" << endl;
				}

			}

		}

	}

	imshow(WINDOW_NAME, copy);

}


int main(int argc, char** argv)
{
	Mat srcImage = imread("3.jpg", 0);                                         //载入原始图二值图模式
	imshow("原始图", srcImage);

	Mat element = getStructuringElement(MORPH_RECT, Size(2, 2));               //定义核，开运算
	morphologyEx(srcImage, srcImage, MORPH_OPEN, element);                    //进行形态学开运算操作

	Mat dstImage = Mat::zeros(srcImage.rows, srcImage.cols, CV_8UC3);         //初始化结果图

	srcImage = srcImage > 50;                                                 //srcImage取大于阈值。。。那部分
	imshow("取阈值后的原始图", srcImage);

	vector<vector<Point> > contours;
	vector<Vec4i> hierarchy;

	findContours(srcImage, contours, hierarchy, RETR_CCOMP, CHAIN_APPROX_SIMPLE);

	int index = 0;                                                           //遍历所有顶层的轮廓， 以随机颜色绘制出每个连接组件颜色
	for (; index >= 0; index = hierarchy[index][0])
	{
		Scalar color(rand() & 255, rand() & 255, rand() & 255);
		drawContours(dstImage, contours, index, color, FILLED, 8, hierarchy);
	}

	system("color 2F");

	g_srcImage = dstImage;
	cvtColor(g_srcImage, g_grayImage, COLOR_BGR2GRAY);

	namedWindow(WINDOW_NAME, WINDOW_AUTOSIZE);                                                                           //创建窗口和滑动条，并进行显示和回调函数初始化
	createTrackbar("最大角点数", WINDOW_NAME, &g_maxCornerNumber, g_maxTrackbarNumber, on_GoodFeaturesToTrack);

	//imshow(WINDOW_NAME, g_srcImage);
	on_GoodFeaturesToTrack(0, 0);

	waitKey(0);
	return 0;
}
结果图：
位置图：
希望有其他方法的小伙伴可以留言。大家相互学习。
opencv 实战，钢板焊接点寻找3

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