基于opencv的卡尺找圆

1. 与卡尺找线的原理一样，只是把直线模型换成了圆模型。直线的在这里基于opencv的卡尺找线
2. 边缘点的筛选还是用RANSNC筛一遍，

void CCaliperGraphics::RansacCircleFiler(const vector<Point2d>& points, vector<Point2d>& vpdExceptPoints, double sigma)
{
    
    
	unsigned int n = points.size();

	if (n < 3)
	{
    
    
		return;
	}

	RNG random;
	double bestScore = -1.;
	vector<Point2d>vpdTemp;
	int iterations = log(1 - 0.99) / (log(1 - (1.00 / n)));

	for (int k = 0; k < iterations; k++)
	{
    
    
		int i1 = 0, i2 = 0, i3 = 0;
		Point2d p1(0, 0), p2(0, 0), p3(0, 0);
		while (true)
		{
    
    
			i1 = random(n);
			i2 = random(n);
			i3 = random(n);
			if ((i1 != i2 && i1 != i3 && i2 != i3))
			{
    
    
				if ((points[i1].y != points[i2].y) && (points[i1].y != points[i3].y))
				{
    
    
					break;
				}
			}
		}
		p1 = points[i1];
		p2 = points[i2];
		p3 = points[i3];

		//use three points to caculate a circle
		Point2d pdP12 = GetPPCenter(p1, p2);
		double dK1 = -1 / GetLineSlope(p1, p2);
		double dB1 = pdP12.y - dK1 * pdP12.x;
		Point2d pdP13 = GetPPCenter(p1, p3);
		double dK2 = -1 / GetLineSlope(p1, p3);
		double dB2 = pdP13.y - dK2 * pdP13.x;
		Point2d pdCenter(0, 0);
		pdCenter.x = (dB2 - dB1) / (dK1 - dK2);
		pdCenter.y = dK1 * pdCenter.x + dB1;
		double dR = GetPPDistance(pdCenter, p1);
		double score = 0;
		vpdTemp.clear();
		for (int i = 0; i < n; i++)
		{
    
    
			double d = dR - GetPPDistance(points[i], pdCenter);
			if (fabs(d) < sigma)
			{
    
    
				score += 1;
			}
			else
			{
    
    
				vpdTemp.push_back(points[i]);
			}
		}
		if (score > bestScore)
		{
    
    
			bestScore = score;
			vpdExceptPoints = vpdTemp;
		}
	}
}

5. opencv只是fitEllipse，圆拟合的算法可以看这个：https://github.com/SohranEliassi/Circle-Fitting-Hyper-Fit，有好几种方法。
6. 效果如下：
   
   基于opencv的卡尺找圆 源码下载

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