C# OpenCvSharp实现通过特征点匹配图片

发布：2024/2/4 14:56:18作者：管理员来源：本站浏览次数：399

SIFT匹配

SURF匹配

项目

代码

SIFT匹配

SURF匹配

项目

代码

using OpenCvSharp;

using OpenCvSharp.Extensions;

using System;

using System.Collections.Generic;

using System.Drawing;

using System.Linq;

using System.Text.RegularExpressions;

using System.Windows.Forms;

using static System.Net.Mime.MediaTypeNames;

namespace OpenCvSharp_Demo

{

public partial class frmMain : Form

{

public frmMain()

{

InitializeComponent();

}

private void Form1_Load(object sender, EventArgs e)

{

}

private void button2_Click(object sender, EventArgs e)

{

Mat matSrc = new Mat("1.jpg");

Mat matTo = new Mat("2.jpg");

var outMat = MatchPicBySift(matSrc, matTo);

pictureBox2.Image = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(outMat);

}

private void button1_Click(object sender, EventArgs e)

{

Mat matSrc = new Mat("1.jpg");

Mat matTo = new Mat("2.jpg");

var outMat = MatchPicBySurf(matSrc, matTo, 10);

pictureBox2.Image = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(outMat);

}

public Point2d Point2fToPoint2d(Point2f point) => new Point2d((double)point.X, (double)point.Y);

public Mat MatchPicBySift(Mat matSrc, Mat matTo)

{

using (Mat matSrcRet = new Mat())

using (Mat matToRet = new Mat())

{

KeyPoint[] keyPointsSrc, keyPointsTo;

using (var sift = OpenCvSharp.Features2D.SIFT.Create())

{

sift.DetectAndCompute(matSrc, null, out keyPointsSrc, matSrcRet);

sift.DetectAndCompute(matTo, null, out keyPointsTo, matToRet);

}

using (var bfMatcher = new OpenCvSharp.BFMatcher())

{

var matches = bfMatcher.KnnMatch(matSrcRet, matToRet, k: 2);

var pointsSrc = new List<Point2f>();

var pointsDst = new List<Point2f>();

var goodMatches = new List<DMatch>();

foreach (DMatch[] items in matches.Where(x => x.Length > 1))

{

if (items[0].Distance < 0.5 * items[1].Distance)

{

pointsSrc.Add(keyPointsSrc[items[0].QueryIdx].Pt);

pointsDst.Add(keyPointsTo[items[0].TrainIdx].Pt);

goodMatches.Add(items[0]);

Console.WriteLine($"{keyPointsSrc[items[0].QueryIdx].Pt.X}, {keyPointsSrc[items[0].QueryIdx].Pt.Y}");

}

var outMat = new Mat();

// 算法RANSAC对匹配的结果做过滤

var pSrc = pointsSrc.ConvertAll(Point2fToPoint2d);

var pDst = pointsDst.ConvertAll(Point2fToPoint2d);

var outMask = new Mat();

// 如果原始的匹配结果为空, 则跳过过滤步骤

if (pSrc.Count > 0 && pDst.Count > 0)

Cv2.FindHomography(pSrc, pDst, HomographyMethods.Ransac, mask: outMask);

// 如果通过RANSAC处理后的匹配点大于10个,才应用过滤. 否则使用原始的匹配点结果(匹配点过少的时候通过RANSAC处理后,可能会得到0个匹配点的结果).

if (outMask.Rows > 10)

{

byte[] maskBytes = new byte[outMask.Rows * outMask.Cols];

outMask.GetArray(out maskBytes);

Cv2.DrawMatches(matSrc, keyPointsSrc, matTo, keyPointsTo, goodMatches, outMat, matchesMask: maskBytes, flags: DrawMatchesFlags.NotDrawSinglePoints);

}

else

Cv2.DrawMatches(matSrc, keyPointsSrc, matTo, keyPointsTo, goodMatches, outMat, flags: DrawMatchesFlags.NotDrawSinglePoints);

return outMat;

}

public Mat MatchPicBySurf(Mat matSrc, Mat matTo, double threshold = 400)

{

using (Mat matSrcRet = new Mat())

using (Mat matToRet = new Mat())

{

KeyPoint[] keyPointsSrc, keyPointsTo;

using (var surf = OpenCvSharp.XFeatures2D.SURF.Create(threshold, 4, 3, true, true))

{

surf.DetectAndCompute(matSrc, null, out keyPointsSrc, matSrcRet);

surf.DetectAndCompute(matTo, null, out keyPointsTo, matToRet);

}

using (var flnMatcher = new OpenCvSharp.FlannBasedMatcher())

{

var matches = flnMatcher.Match(matSrcRet, matToRet);

//求最小最大距离

double minDistance = 1000;//反向逼近

double maxDistance = 0;

for (int i = 0; i < matSrcRet.Rows; i++)

{

double distance = matches[i].Distance;

if (distance > maxDistance)

{

maxDistance = distance;

}

if (distance < minDistance)

{

minDistance = distance;

}

Console.WriteLine($"max distance : {maxDistance}");

Console.WriteLine($"min distance : {minDistance}");

var pointsSrc = new List<Point2f>();

var pointsDst = new List<Point2f>();

//筛选较好的匹配点

var goodMatches = new List<DMatch>();

for (int i = 0; i < matSrcRet.Rows; i++)

{

double distance = matches[i].Distance;

if (distance < Math.Max(minDistance * 2, 0.02))

{

pointsSrc.Add(keyPointsSrc[matches[i].QueryIdx].Pt);

pointsDst.Add(keyPointsTo[matches[i].TrainIdx].Pt);

//距离小于范围的压入新的DMatch

goodMatches.Add(matches[i]);

}