OpenCVSharp入门教程特征提取③——HoughLinesP直线寻找，直线提取

忘是亡心i 2023-01-24 04:25 14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 HoughLinesP直线提取—源码
     *  4.3 HoughLinesP直线提取—参数讲解
 *  五、运行效果图
 *  六、参考

# 一、前文 #

> Hough变换  
> 经典的直线检测算法

# 二、算法流程 #

1.  高斯模糊
2.  Canny边缘检测
3.  HoughLinesP直线寻找，直线提取

# 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 HoughLinesP直线提取—源码 ##

private void houghLinesBtn_Click(object sender, EventArgs e)
    { 
        cannyBtn_Click(sender, e);
        mOutput = new Mat(mInput.Rows, mInput.Cols, MatType.CV_8UC4);
        mInput.CopyTo(mOutput);
    
        double rho = 1;
        double theta = 1;
        int threshold = 10;
        double minLineLength = 0;
        double maxLineGap = 0;
    
        var res = Cv2.HoughLinesP(edges,
            rho: rho,
            theta: theta / 100.0,
            threshold: threshold,
            minLineLength: minLineLength,
            maxLineGap: maxLineGap);
    
        for (int i = 0; i < res.Length; i++)
        { 
            Scalar color = Scalar.RandomColor();
            Cv2.Line(mOutput, res[i].P1, res[i].P2,
                color: color,
                thickness: 2,
                lineType: LineTypes.Link8);
        }
    
        srcPictureBox.Image = BitmapConverter.ToBitmap(mInput);
        grayPictureBox.Image = BitmapConverter.ToBitmap(edges);
        dstPictureBox.Image = BitmapConverter.ToBitmap(mOutput);
    }

## 4.3 HoughLinesP直线提取—参数讲解 ##

//
    // 摘要:
    // Finds lines segments in a binary image using probabilistic Hough transform.
    //
    // 参数:
    // image:
    //
    // rho:
    // Distance resolution of the accumulator in pixels
    //
    // theta:
    // Angle resolution of the accumulator in radians
    //
    // threshold:
    // The accumulator threshold parameter. Only those lines are returned that get enough
    // votes ( > threshold )
    //
    // minLineLength:
    // The minimum line length. Line segments shorter than that will be rejected. [By
    // default this is 0]
    //
    // maxLineGap:
    // The maximum allowed gap between points on the same line to link them. [By default
    // this is 0]
    //
    // 返回结果:
    // The output lines. Each line is represented by a 4-element vector (x1, y1, x2,
    // y2)
    public static LineSegmentPoint[] HoughLinesP(InputArray image, double rho, double theta, int threshold, double minLineLength = 0, double maxLineGap = 0);

*  `image`，灰度图片输入
 *  `rho`，步长为1的半径
 *  `theta`，步长为π/180的角来，来搜索所有可能的直线
 *  `threshold`，阈值，大于阈值 threshold 的线段才可以被确认为直线。该值越小，判定出的直线越多；值越大，判定出的直线就越少。
 *  `minLineLength`，线段的最短长度，长度小于该值的线段会被忽略
 *  `maxLineGap`，两条线段之间的最大间隔，间隔小于该值的两条线会被当成一条线

# 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HoughLinesP直线提取的结果图

![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—直线检测][OpenCV]

***觉得好，就一键三连呗（点赞+收藏+关注）***

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[OpenCV]: https://www.cnblogs.com/ssyfj/p/9275368.html