OpenCVSharp入门教程特征提取②——FindContours寻找轮廓，轮廓提取

短命女 2023-01-24 04:22 103阅读 0赞

### 文章目录 ###

*  一、前文
 *  二、算法流程
 *  三、界面布局
 *  四、功能实现
 *   *  4.1 打开图片
     *  4.2 FindContours轮廓提取—源码
     *  4.3 FindContours轮廓提取—参数讲解
 *  五、运行效果图
 *  六、参考

# 一、前文 #

> 基于边缘检测算法的轮廊寻找和提取

# 二、算法流程 #

1.  高斯模糊
2.  Canny边缘检测
3.  FindContours寻找轮廓，轮廊提取

# 三、界面布局 #

*  一个`Label`
 *  N个`Button`
 *  三个`Picture`

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2thbmd3ZWlqaWFu_size_16_color_FFFFFF_t_70]

# 四、功能实现 #

## 4.1 打开图片 ##

private void openFileBtn_Click(object sender, EventArgs e)
     { 
         OpenFileDialog openfiledialog = new OpenFileDialog();
         openfiledialog.Filter = "PNG Files (*.png)|*.png|JPG Files (*.jpg)|*.jpg|GIF Files (*.gif)|*.gif";
         openfiledialog.RestoreDirectory = true;
         if (openfiledialog.ShowDialog() == DialogResult.OK)
         { 
             Console.WriteLine(openfiledialog.FileName);
             fileName = openfiledialog.FileName;
    
             //Mat src = new Mat("foo.png", LoadMode.Color);
             Mat src = new Mat(fileName);
             //Mat src = new Mat(fileName, ImreadModes.Color);
             var frameBitmap = BitmapConverter.ToBitmap(src);
    
             pictureBox1.Image?.Dispose();
             pictureBox1.Image = frameBitmap;
         }
     }

## 4.2 FindContours轮廓提取—源码 ##

private void contoursBtn_Click(object sender, EventArgs e)
    { 
        cannyBtn_Click(sender, e);
        mOutput = new Mat(mInput.Rows, mInput.Cols, MatType.CV_8UC4);
        mInput.CopyTo(mOutput);
    
        RetrievalModes mode = RetrievalModes.External;
        ContourApproximationModes method = ContourApproximationModes.ApproxNone;
        Point offset = new OpenCvSharp.Point(0, 0);
    
        Cv2.FindContours(
            image: edges,
            contours: out OpenCvSharp.Point[][] contours,
            hierarchy: out HierarchyIndex[] outputArray,
            mode: mode,
            method: method,
            offset: offset);
    
        for (int i = 0; i < contours.Length; i++)
        { 
            Scalar color = Scalar.RandomColor();
            if (contours[i].Length > 100)
            { 
                Cv2.DrawContours(
                    mOutput,
                    contours,
                    contourIdx: i,
                    color: color,
                    thickness: 2,
                    lineType: LineTypes.Link8,
                    hierarchy: outputArray,
                    maxLevel: 0);
            }
        }
    
        srcPictureBox.Image = BitmapConverter.ToBitmap(mInput);
        grayPictureBox.Image = BitmapConverter.ToBitmap(edges);
        dstPictureBox.Image = BitmapConverter.ToBitmap(mOutput);
    }

## 4.3 FindContours轮廓提取—参数讲解 ##

//
    // 摘要:
    // Finds contours in a binary image.
    //
    // 参数:
    // image:
    // Source, an 8-bit single-channel image. Non-zero pixels are treated as 1’s. Zero
    // pixels remain 0’s, so the image is treated as binary. The function modifies the
    // image while extracting the contours.
    //
    // contours:
    // Detected contours. Each contour is stored as a vector of points.
    //
    // hierarchy:
    // Optional output vector, containing information about the image topology. It has
    // as many elements as the number of contours. For each i-th contour contours[i],
    // the members of the elements hierarchy[i] are set to 0-based indices in contours
    // of the next and previous contours at the same hierarchical level, the first child
    // contour and the parent contour, respectively. If for the contour i there are
    // no next, previous, parent, or nested contours, the corresponding elements of
    // hierarchy[i] will be negative.
    //
    // mode:
    // Contour retrieval mode
    //
    // method:
    // Contour approximation method
    //
    // offset:
    // Optional offset by which every contour point is shifted. This is useful if the
    // contours are extracted from the image ROI and then they should be analyzed in
    // the whole image context.
    public static void FindContours(InputArray image, out Point[][] contours, out HierarchyIndex[] hierarchy, RetrievalModes mode, ContourApproximationModes method, Point? offset = null);

*  `image`，灰度图片输入
 *  `contours`，轮廓结果输出
 *  `mode`，轮廓检索模式
    
     *  `External`，只检测外层轮廓
     *  `List`，提取所有轮廓，并放置在list中，检测的轮廓不建立等级关系
     *  `CComp`，提取所有轮廓，并将轮廓组织成双层结构(two-level hierarchy),顶层为连通域的外围边界，次层位内层边界
     *  `Tree`，提取所有轮廓并重新建立网状轮廓结构
     *  `FloodFill`，官网没有介绍，应该是洪水填充法
 *  `method`，轮廓近似方法
    
     *  `ApproxNone`，获取每个轮廓的每个像素，相邻的两个点的像素位置差不超过1
     *  `ApproxSimple`，压缩水平方向，垂直方向，对角线方向的元素，值保留该方向的重点坐标，如果一个矩形轮廓只需4个点来保存轮廓信息
     *  `ApproxTC89L1`，使用Teh-Chinl链逼近算法中的一种
     *  `ApproxTC89KCOS`，使用Teh-Chinl链逼近算法中的一种

# 五、运行效果图 #

从左到右

*  第一张是原图
 *  第二张是高斯模糊的结果图
 *  第三张是FindContours轮廊提取的结果图

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2thbmd3ZWlqaWFu_size_16_color_FFFFFF_t_70 1]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2thbmd3ZWlqaWFu_size_16_color_FFFFFF_t_70 2]

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2thbmd3ZWlqaWFu_size_16_color_FFFFFF_t_70 3]

# 六、参考 #

[OpenCV—轮廓发现][OpenCV]

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[OpenCV]: https://www.cnblogs.com/ssyfj/p/9276443.html