如何实现视觉识别形状

机器谱 · 发表于 2023-4-14 09:51:43

本帖最后由机器谱于 2023-4-14 09:51 编辑

1. 功能说明
通过摄像头识别圆形及矩形两种形状。

2. 电子硬件
本实验中采用了以下硬件：

主控板	Basra主控板（兼容Arduino Uno）
扩展板	Bigfish2.1扩展板
电池	7.4V锂电池
通信	2510通信转接板
通信	WiFi路由器
其它	摄像头
其它	配置OpenCV的Visual Studio 2015.net环境的计算机一台

3. 功能实现
工作原理：
      ① 导入一张图片或者通过WiFi传递摄像信息给PC；
      ② 在PC端使用OpenCV对图像转化为灰度图像；
      ③ 检测圆形和矩形。
检测圆形使用霍夫变换：

vector<Vec3f> circles;
HoughCircles(image, circles, HOUGH_GRADIENT, 2.0,
image.rows/8, // change this value to detect circles with different distances to each other
200, 85, 0, 0 // change the last two parameters
// (min_radius & max_radius) to detect larger circles
);

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检测矩形：

//多边形检测，通过约束条件寻找矩形
static void findSquares(const Mat& image, vector<vector<Point> >& squares)
{
squares.clear();
Mat pyr, timg, gray0(image.size(), CV_8U), gray;
// down-scale and upscale the image to filter out the noise
pyrDown(image, pyr, Size(image.cols / 2, image.rows / 2));
pyrUp(pyr, timg, image.size());
vector<vector<Point> > contours;
// find squares in every color plane of the image
for (int c = 0; c < 3; c++)
{
int ch[] = { c, 0 };
mixChannels(&timg, 1, &gray0, 1, ch, 1);
// try several threshold levels
for (int l = 0; l < N; l++)
{
// hack: use Canny instead of zero threshold level.
// Canny helps to catch squares with gradient shading
if (l == 0)
{
// apply Canny. Take the upper threshold from slider
// and set the lower to 0 (which forces edges merging)
Canny(gray0, gray, 0, thresh, 5);
// dilate canny output to remove potential
// holes between edge segments
dilate(gray, gray, Mat(), Point(-1, -1));
}
else
{
// apply threshold if l!=0:
// tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
gray = gray0 >= (l + 1) * 255 / N;
}
// find contours and store them all as a list
findContours(gray, contours, RETR_LIST, CHAIN_APPROX_SIMPLE);
vector<Point> approx;
// test each contour
for (size_t i = 0; i < contours.size(); i++)
{
// approximate contour with accuracy proportional
// to the contour perimeter
approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true)*0.02, true);
// square contours should have 4 vertices after approximation
// relatively large area (to filter out noisy contours)
// and be convex.
// Note: absolute value of an area is used because
// area may be positive or negative - in accordance with the
// contour orientation
if (approx.size() == 4 &&
fabs(contourArea(Mat(approx))) > 1000 &&
isContourConvex(Mat(approx)))
{
double maxCosine = 0;
for (int j = 2; j < 5; j++)
{
// find the maximum cosine of the angle between joint edges
double cosine = fabs(angle(approx[j % 4], approx[j - 2], approx[j - 1]));
maxCosine = MAX(maxCosine, cosine);
}
// if cosines of all angles are small
// (all angles are ~90 degree) then write quandrange
// vertices to resultant sequence
if (maxCosine < 0.3)
squares.push_back(approx);
}
}
}
}
}

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3.1硬件连接
将摄像头与路由器连接，启动路由器，将PC连接到路由器的WIFI网络。

接线说明：
   ① 将2510通信转接板连接到扩展板的扩展坞上面；
   ② 用3根母对母杜邦线将2510通信转接板与WiFi路由器连接起来，GND-GND、RX-RX、TX-TX；
   ③ 找到1根USB线，一端连接到2510通信转接板接口上，另一端连接到WiFi路由器USB接口上；
   ④ 将摄像头线连接到WiFi路由器接口上。

3.2示例程序
   下面提供一个可以进行识别圆形和矩形的参考例程（ShapeDetect\ShapeDetect\MainWindow.xaml.cs）：

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Windows;
using System.Windows.Controls;
using System.Windows.Data;
using System.Windows.Documents;
using System.Windows.Input;
using System.Windows.Media;
using System.Windows.Media.Imaging;
using System.Windows.Navigation;
using System.Windows.Shapes;
using System.Windows.Forms;
using System.Runtime.InteropServices;
using System.Threading;
namespace ShapeDetect
{
/// <summary>
/// 形状识别
/// </summary>
public partial class MainWindow : Window
{
//定义检测模式
int IMAGE_MODE = 1, VIDEO_MODE = 2;
private AutoResetEvent exitEvent;
private Thread m_thread;
//导入动态链接库
[DllImport("HoughCircles_DLL.dll")]
//检测圆
public static extern System.UIntPtr HoughCircles([MarshalAs(UnmanagedType.LPStr)]string address, int detect_mode);
[DllImport("SquareDetect_DLL.dll")]
//检测矩形
public static extern void SquareDetector([MarshalAs(UnmanagedType.LPStr)]string address, int detect_mode);
public MainWindow()
{
InitializeComponent();
}
private void Window_Loaded(object sender, RoutedEventArgs e)
{
GetIni();
imgCheckBtn.IsChecked = true;
circleCheckBtn.IsChecked = true;
}
//获取ini配置文件信息
private void GetIni()
{
ini_RW.FileName = System.Windows.Forms.Application.StartupPath + "\\Config.ini";
this.videoAddress.Text = ini_RW.ReadIni("VideoUrl", "videourl", "");
this.ipAddress.Text = ini_RW.ReadIni("ControlUrl", "controlUrl", "");
this.portBox.Text = ini_RW.ReadIni("ControlPort", "controlPort", "");
}
//修改配置
private void setBtn_Click(object sender, RoutedEventArgs e)
{
ini_RW.WriteIni("VideoUrl", "videourl", this.videoAddress.Text);
ini_RW.WriteIni("ControlUrl", "controlUrl", this.ipAddress.Text);
ini_RW.WriteIni("ControlPort", "controlPort", this.portBox.Text);
System.Windows.MessageBox.Show("配置成功！请重启程序以使配置生效。", "配置信息", MessageBoxButton.OK, MessageBoxImage.Information);
//this.Close();
}
//计数清零
private void BoxClean()
{
circleTextBox.Text = "0";
recTextBox.Text = "0";
}
//打开图片地址
private void imgBtn_Click(object sender, RoutedEventArgs e)
{
try
{
BoxClean();
//WPF中，OpenFileDialog位于Microsoft.Win32名称空间
Microsoft.Win32.OpenFileDialog dialog = new Microsoft.Win32.OpenFileDialog();
dialog.Filter = "All files (*.*)|*.*|jpg files (*.jpg)|*.jpg|png files(*.png)|*.png";
if (dialog.ShowDialog() == true)
{
string path = dialog.FileName;
imgAddressBox.Text = path;
}
}
catch { };
}
//检测形状判断
private void ShapeDetect(string address, int mode)
{
if (circleCheckBtn.IsChecked == true)
{
//System.Windows.MessageBox.Show("检测圆形");
circleTextBox.Text = HoughCircles(address, mode).ToString();
}
else if (recCheckBtn.IsChecked == true)
{
//System.Windows.MessageBox.Show("检测矩形");
SquareDetector(address, mode);
}
}
//图片检测
private void imgDetect()
{
if (imgAddressBox.Text == string.Empty)
{
System.Windows.MessageBox.Show(
"图片地址为空，请选择一张图片", "警告",
MessageBoxButton.OK,
MessageBoxImage.Information
);
return;
}
else
{
ShapeDetect(imgAddressBox.Text, IMAGE_MODE);
}
}
//视频检测
private void videoDetect()
{
try
{
while (true)
{
this.Dispatcher.Invoke(
new Action(
delegate
{
string ip = this.videoAddress.Text;
ShapeDetect(ip, VIDEO_MODE);
}
));
}
}
catch { };
}
//判断检测为图片还是视频，开启形状检测
private void detectBtn_Click(object sender, RoutedEventArgs e)
{
BoxClean();
if (imgCheckBtn.IsChecked == true)
{
imgDetect();
}
else if (videoCheckBtn.IsChecked == true)
{
try
{
m_thread = new Thread(new ThreadStart(videoDetect));
m_thread.Start();
}
catch { };
}
}
//按esc键退出视频检测，结束线程
private void Window_KeyDown(object sender, System.Windows.Input.KeyEventArgs e)
{
if (e.Key == Key.Escape)
{
exitEvent.Set();
m_thread.Join();
}
}
}
}

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程序识别圆形及矩形两种形状，包括对图像以及视频中的物体的形状检测，可参考上面的演示视频进行操作。图片中物体的形状识别，文末资料下载中提供一张测试图片，然后选择图片按钮，选择要检测的圆形或者矩形，点击形状检测。

视频中的形状识别，选择视频按钮，选择要检测的圆形或者矩形，点击形状检测，可以使用球体或者矩形状物体进行检测。

4. 资料下载
资料内容：
①识别形状-例程源代码
②测试图片.jpg
资料下载地址：https://www.robotway.com/h-col-200.html

想了解更多机器人开源项目资料请关注机器谱网站 https://www.robotway.com

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