EmgnCv进行轮廓寻找和计算物体凸包-白红宇

EmgnCv进行轮廓寻找和计算物体凸包

阅读量：5878 次

发布时间：2019-06-19

本文共 3880 字，大约阅读时间需要 12 分钟。

http://blog.csdn.net/qq_22033759/article/details/48029493

一、轮廓寻找

用的是FindContours函数，在CvInvoke中

不过需要用到这个VectorOfVectorOfPoint，来代替c++中的Vector

还有就是FindContours函数中的第三个参数hierarchy，不知道作用是什么，填入的只要是符合IOutputArray类型的都可以运行

代码：

using System;using System.Collections.Generic;using System.ComponentModel;using System.Data;using System.Drawing; using System.Linq; using System.Text; using System.Threading.Tasks; using System.Windows.Forms; using Emgu.CV; using Emgu.CV.CvEnum; using Emgu.CV.Structure; using Emgu.CV.Util; using Emgu.Util; using Emgu.CV.UI; namespace EmguCVHist { public partial class Form1 : Form { public Form1() { InitializeComponent(); Image
    
      a = new Image
     
      ("153_140703112619_1.jpg"); Image
      
        b = new Image
       
        (a.Width, a.Height); Image
        
          c = new Image
         
          (a.Width, a.Height); Image
          
            d = new Image
           
            (a.Width, a.Height); CvInvoke.Canny(a, b, 100, 60); VectorOfVectorOfPoint con = new VectorOfVectorOfPoint(); CvInvoke.FindContours(b, con, c, RetrType.Ccomp, ChainApproxMethod.ChainApproxSimple); for (int i = 0; i < con.Size; i++) CvInvoke.DrawContours(d, con, i, new MCvScalar(255, 0, 255, 255),2); imageBox1.Image = d; } } }

这里写图片描述

二、凸包的计算

凸包的计算需要用到上面所求得的轮廓寻找的数据

ConvexHull函数的参数之前的不太一样，换成了PointF类型的，但所求的数据为VectorOfVectorOfPoint类型，所以就需要个转换，先把VectorOfVectorOfPoint转为Point的二维数组，在把二维数组转成PointF的二维数组，然后再挨个调用，

代码如下：

using System;using System.Collections.Generic;using System.ComponentModel;using System.Data;using System.Drawing; using System.Linq; using System.Text; using System.Threading.Tasks; using System.Windows.Forms; using Emgu.CV; using Emgu.CV.CvEnum; using Emgu.CV.Structure; using Emgu.CV.Util; using Emgu.Util; using Emgu.CV.UI; namespace EmguCVHist { public partial class Form1 : Form { public Form1() { InitializeComponent(); Image
    
      a = new Image
     
      ("9660416_102608612175_2.jpg"); Image 
      
        b = new Image
       
        (a.Width, a.Height); Image
        
          c = new Image
         
          (a.Width, a.Height); Image
          
            d = new Image
           
            (a.Width, a.Height); CvInvoke.Canny(a, b, 100, 60); VectorOfVectorOfPoint con = new VectorOfVectorOfPoint(); CvInvoke.FindContours(b, con, c, RetrType.Ccomp, ChainApproxMethod.ChainApproxSimple); Point[][] con1 = con.ToArrayOfArray(); PointF[][] con2 = Array.ConvertAll
            
             (con1, new Converter
             
              (PointToPointF)); for (int i = 0; i < con.Size; i++) { PointF[] hull = CvInvoke.ConvexHull(con2[i], true); for (int j = 0; j < hull.Length; j++) { Point p1 = new Point((int)(hull[j].X + 0.5), (int)(hull[j].Y + 0.5)); Point p2; if (j == hull.Length - 1) p2 = new Point((int)(hull[0].X + 0.5), (int)(hull[0].Y + 0.5)); else p2 = new Point((int)(hull[j + 1].X + 0.5), (int)(hull[j + 1].Y + 0.5)); CvInvoke.Circle(d, p1, 3, new MCvScalar(0, 255, 255, 255), 6); CvInvoke.Line(d, p1, p2, new MCvScalar(255, 255, 0, 255), 3); } } for (int i = 0; i < con.Size; i++) CvInvoke.DrawContours(d, con, i, new MCvScalar(255, 0, 255, 255), 2); imageBox1.Image = a.ConcateVertical(d); } public static PointF[] PointToPointF(Point[] pf) { PointF[] aaa = new PointF[pf.Length]; int num = 0; foreach(var point in pf) { aaa[num].X = (int)point.X; aaa[num++].Y = (int)point.Y; } return aaa; } } }

运行图：（之前那个图片由于会被分为好多块，所以换了张图片）

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