基于C#和OpenCV的双目视觉三维空间构建

C#和OpenCV的双目视觉三维空间构建实现。包括相机标定、立体校正、视差计算和三维重建。

1. 环境准备

确保你已经安装了以下工具和库：

• Visual Studio：用于开发C#应用程序。
• OpenCV：用于图像处理和计算机视觉任务。
• Emgu.CV：OpenCV的C#封装库，可以通过NuGet安装。

2. 安装Emgu.CV

在Visual Studio中，通过NuGet包管理器安装Emgu.CV库。在解决方案资源管理器中右键单击项目名称，选择“管理NuGet程序包”，搜索并安装Emgu.CV。

3. 核心代码实现

3.1 相机标定

相机标定是双目视觉系统的基础，用于获取相机的内参和外参。以下代码展示了如何使用OpenCV进行相机标定。

using Emgu.CV;
using Emgu.CV.Structure;
using Emgu.CV.Util;
using System;
using System.Collections.Generic;

public class CameraCalibration
{
    public static void CalibrateCamera(string leftImagesPath, string rightImagesPath, Size boardSize, float squareSize, out Matrix<double> K1, out Matrix<double> D1, out Matrix<double> K2, out Matrix<double> D2, out Matrix<double> R, out Matrix<double> T, out Matrix<double> E, out Matrix<double> F)
    {
        List<Image<Gray, byte>> leftImages = LoadImages(leftImagesPath);
        List<Image<Gray, byte>> rightImages = LoadImages(rightImagesPath);

        List<Point3f[]> objectPoints = new List<Point3f[]>();
        List<Point2f[]> leftImagePoints = new List<Point2f[]>();
        List<Point2f[]> rightImagePoints = new List<Point2f[]>();

        for (int i = 0; i < leftImages.Count; i++)
        {
            Point3f[] objp = new Point3f[boardSize.Width * boardSize.Height];
            for (int j = 0; j < boardSize.Height; j++)
            {
                for (int k = 0; k < boardSize.Width; k++)
                {
                    objp[j * boardSize.Width + k] = new Point3f(k * squareSize, j * squareSize, 0);
                }
            }
            objectPoints.Add(objp);

            bool foundLeft = CvInvoke.FindChessboardCorners(leftImages[i], boardSize, out Point2f[] cornersLeft, ChessboardFlag.AdaptiveThresh | ChessboardFlag.NormalizeImage);
            bool foundRight = CvInvoke.FindChessboardCorners(rightImages[i], boardSize, out Point2f[] cornersRight, ChessboardFlag.AdaptiveThresh | ChessboardFlag.NormalizeImage);

            if (foundLeft && foundRight)
            {
                leftImagePoints.Add(cornersLeft);
                rightImagePoints.Add(cornersRight);
            }
        }

        CvInvoke.StereoCalibrate(objectPoints.ToArray(), leftImagePoints.ToArray(), rightImagePoints.ToArray(), out K1, out D1, out K2, out D2, leftImages[0].Size, out R, out T, out E, out F, CalibrationFlag.FixK4 | CalibrationFlag.FixK5);
    }

    private static List<Image<Gray, byte>> LoadImages(string path)
    {
        List<Image<Gray, byte>> images = new List<Image<Gray, byte>>();
        // Load images from directory
        return images;
    }
}

3.2 立体校正

立体校正用于对齐左右图像，以便后续的视差计算。

using Emgu.CV;
using Emgu.CV.Structure;
using Emgu.CV.Util;
using System;

public class StereoRectification
{
    public static void RectifyImages(Matrix<double> K1, Matrix<double> D1, Matrix<double> K2, Matrix<double> D2, Matrix<double> R, Matrix<double> T, Size imageSize, out Matrix<double> R1, out Matrix<double> R2, out Matrix<double> P1, out Matrix<double> P2, out Matrix<double> Q)
    {
        CvInvoke.StereoRectify(K1, D1, K2, D2, imageSize, R, T, out R1, out R2, out P1, out P2, out Q, StereoRectifyFlag.ZeroDisparity, 0, imageSize);
    }
}

3.3 视差计算

视差计算是双目视觉的核心步骤，用于生成深度图。

using Emgu.CV;
using Emgu.CV.Structure;
using Emgu.CV.Util;
using System;

public class DisparityCalculation
{
    public static void ComputeDisparity(Image<Gray, byte> leftImage, Image<Gray, byte> rightImage, out Image<Gray, byte> disparityMap)
    {
        StereoBM stereo = new StereoBM(16, 15);
        stereo.Compute(leftImage, rightImage, out disparityMap);
    }
}

3.4 三维重建

根据视差图和相机参数，可以重建三维点云。

using Emgu.CV;
using Emgu.CV.Structure;
using Emgu.CV.Util;
using System;

public class ThreeDReconstruction
{
    public static void Reconstruct3D(Image<Gray, byte> disparityMap, Matrix<double> Q, out Image<Point3f> points3D)
    {
        points3D = CvInvoke.ReprojectImageTo3D(disparityMap, Q);
    }
}

4. 主程序

将上述模块组合起来，实现完整的双目视觉三维重建流程。

using Emgu.CV;
using Emgu.CV.Structure;
using Emgu.CV.Util;
using System;

public class Program
{
    public static void Main(string[] args)
    {
        Matrix<double> K1, D1, K2, D2, R, T, E, F;
        CameraCalibration.CalibrateCamera("left_images_path", "right_images_path", new Size(7, 7), 1.0, out K1, out D1, out K2, out D2, out R, out T, out E, out F);

        Matrix<double> R1, R2, P1, P2, Q;
        StereoRectification.RectifyImages(K1, D1, K2, D2, R, T, new Size(640, 480), out R1, out R2, out P1, out P2, out Q);

        Image<Gray, byte> leftImage = new Image<Gray, byte>("left_image.png");
        Image<Gray, byte> rightImage = new Image<Gray, byte>("right_image.png");

        Image<Gray, byte> disparityMap;
        DisparityCalculation.ComputeDisparity(leftImage, rightImage, out disparityMap);

        Image<Point3f> points3D;
        ThreeDReconstruction.Reconstruct3D(disparityMap, Q, out points3D);

        // Save or display the 3D points
    }
}

参考代码 C#编程，OpenCV,双目视觉，构建三维空间 www.youwenfan.com/contentcne/111961.html

基于C#和OpenCV的双目视觉三维空间构建系统。可根据实际需求，可以进一步优化和扩展代码。