opencv不规则物体宽度测量

头文件：

#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include 
#include 
#include 
#include 
#define pi 3.1415926

using namespace cv;
using namespace std;

滤波函数：

void RemoveSmallRegion(Mat& Src, Mat& Dst, int AreaLimit, int AreaTop, int CheckMode, int NeihborMode)
{
	int RemoveCount = 0;       //记录除去的个数  
							   //记录每个像素点检验状态的标签，0代表未检查，1代表正在检查,2代表检查不合格（需要反转颜色），3代表检查合格或不需检查  
	Mat Pointlabel = Mat::zeros(Src.size(), CV_8UC1);

	if (CheckMode == 1)
	{
		//cout<<"Mode: 去除小区域. ";  
		for (int i = 0; i < Src.rows; ++i)
		{
			uchar* iData = Src.ptr(i);
			uchar* iLabel = Pointlabel.ptr(i);
			for (int j = 0; j < Src.cols; ++j)
			{
				if (iData[j] < 10)
				{
					iLabel[j] = 3;
				}
			}
		}
	}
	else
	{
		//cout<<"Mode: 去除孔洞. ";  
		for (int i = 0; i < Src.rows; ++i)
		{
			uchar* iData = Src.ptr(i);
			uchar* iLabel = Pointlabel.ptr(i);
			for (int j = 0; j < Src.cols; ++j)
			{
				if (iData[j] > 10)
				{
					iLabel[j] = 3;
				}
			}
		}
	}

	vector NeihborPos;  //记录邻域点位置  
	NeihborPos.push_back(Point2i(-1, 0));
	NeihborPos.push_back(Point2i(1, 0));
	NeihborPos.push_back(Point2i(0, -1));
	NeihborPos.push_back(Point2i(0, 1));
	if (NeihborMode == 1)
	{
		//cout<<"Neighbor mode: 8邻域."<(i);
		for (int j = 0; j < Src.cols; ++j)
		{
			if (iLabel[j] == 0)
			{
				//********开始该点处的检查**********  
				vector GrowBuffer;                                      //堆栈，用于存储生长点  
				GrowBuffer.push_back(Point2i(j, i));
				Pointlabel.at(i, j) = 1;
				int CheckResult = 0;                                               //用于判断结果（是否超出大小），0为未超出，1为超出  

				for (int z = 0; z= 0 && CurrX= 0 && CurrY(CurrY, CurrX) == 0)
							{
								GrowBuffer.push_back(Point2i(CurrX, CurrY));  //邻域点加入buffer  
								Pointlabel.at(CurrY, CurrX) = 1;           //更新邻域点的检查标签，避免重复检查  
							}
						}
					}

				}
				if ((int(GrowBuffer.size())>AreaLimit)&(int(GrowBuffer.size())(CurrY, CurrX) += CheckResult;
				}
				//********结束该点处的检查**********  


			}
		}
	}

	CheckMode = 255 * (1 - CheckMode);
	//开始反转面积过小的区域  
	for (int i = 0; i < Src.rows; ++i)
	{
		uchar* iData = Src.ptr(i);
		uchar* iDstData = Dst.ptr(i);
		uchar* iLabel = Pointlabel.ptr(i);
		for (int j = 0; j < Src.cols; ++j)
		{
			if (iLabel[j] == 2)
			{
				iDstData[j] = CheckMode;
			}
			else if (iLabel[j] == 3)
			{
				iDstData[j] = iData[j];
			}
		}
	}

	//cout<

主函数：

1. 在获得的烟草区域内选取任意一点，以该点画圆，半径逐步增加，设定条件（在该圆中的烟草区域/圆的面积<某阈值），当不符合时，将圆进行空白区域中心的反向半径方向移动，直到满足条件（设定最大移动范围）；
2. 以此方法，在宽度方向上获得最大内接圆，烟草宽度即为圆的直径；
3. 相同方法取多点，分别检测宽度（阈值），最后计算均值；

int main()
{
	char filename[100];
	for (int w = 1; w <= 1; w++)//
	{
		sprintf_s(filename, "../../准确性/1.bmp", w);//../../重复性/11-%d.bmp
		cout << filename<<"    ";
		Mat imgsrc = imread(filename, 1);
		Mat img_gray, img_by, img_by1;
		cvtColor(imgsrc, img_gray, CV_BGR2GRAY);//彩色转灰度图
		adaptiveThreshold(img_gray, img_by, 255, ADAPTIVE_THRESH_MEAN_C, CV_THRESH_BINARY_INV, 9, 10);
		RemoveSmallRegion(img_by, img_by, 100, 3000, 1, 0);

		vector> contours;
		findContours(img_by, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE);//查找最外侧轮廓
		//1最大外接圆
		//int dist = 0;
		//int maxdist = 0;
		//Point center;
		//for (int i = 0; imaxdist)
		//		{
		//			maxdist = dist;
		//			center = cv::Point(i, j);
		//		}
		//	}
		//}
		//circle(img_by, center, maxdist, Scalar(0),-1);
		//imshow("zc", img_gray);

		//2
		for (int q = 0; q < contours.size(); q++)
		{
			RNG rng;//随机数
			Point2f point;
			double radius_all = 0;
			for (int p = 0; p < 4; p++)
			{
				int num = rng.uniform(0, contours[q].size());
				point = Point2f(contours[q][num].x, contours[q][num].y);//随机点

				double radius;//半径
				double resulit_limit = 0.9;

				for (radius = 2.0; radius < 5.0; radius += 0.1)//随机圆变化起点
				{
					int baidian_num = 0;
					int baidian_x = 0;
					int baidian_y = 0;
				restart:
					for (int i = point.y - radius; i < point.y + radius; i++)//计算区域在圆内像素个数
						for (int j = point.x - radius; j < point.x + radius; j++)
						{
							if (img_by.at(i, j) == 255 && ((point.y - i)*(point.y - i) + (point.x - j)*(point.x - j) < radius*radius))
							{
								baidian_num++;
								baidian_x += j;
								baidian_y += i;
							}
						}
					double result = baidian_num / (pi*radius*radius);//计算占比
					if (result < resulit_limit)//移动圆心位置
					{
						point.x = point.x + (baidian_x / baidian_num - point.x) / 2;//x方向
						point.y = point.y + (baidian_y / baidian_num - point.y) / 2;//y方向
						goto restart;
					}
					else if ((result > resulit_limit) && (result < 1))
					{
						if ((baidian_x / baidian_num - point.x) *(baidian_x / baidian_num - point.x) + (baidian_y / baidian_num - point.y) * (baidian_y / baidian_num - point.y) < 0.5)
							break;
					}
					else if (result == 1)
						continue;//半径自增	
				}
				radius_all += radius;

			}
			cout << radius_all / 4.0 * 2.0 << "  pixels" << endl;
		}


	}

	system("pause");
}

测试图像：

运行结果：