AoiMarkMethod.cs
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using System;
using System.Collections.Generic;
using System.Drawing;
using System.Drawing.Drawing2D;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using OpenCvSharp;
using OpenCvSharp.XFeatures2D;
namespace AOI
{
/// <summary>
/// 从搜索区域中查找Mark区域,对图片进行校准
/// </summary>
public class AoiMarkMethod : AoiMethod
{
/// <summary>
/// 搜索区域路径
/// </summary>
public GraphicsPath SearchPath;
public override ResultBean Check(Image standardImage, Image imageToCheck)
{
ResultBean resultBean = new ResultBean();
resultBean.standardRoiImage = standardImage;
bool needCut = false;
//标准图中的Mart区域
Image markImage = GetRoiImage(standardImage, RoiPath, needCut);
//搜索区域
Image searchImage = GetRoiImage(imageToCheck, SearchPath, needCut);
if (markImage != null && searchImage != null)
{
var affine = GetAffineMat(markImage, searchImage);
if(affine != null)
{
var matToCheck = ImageUtil.ToMat(imageToCheck);
var fixedMat = FixImage(affine, matToCheck);
resultBean.result = true;
resultBean.currentRoiImage = ImageUtil.ToImage(fixedMat);
}
}
return resultBean;
}
/// <summary>
/// 校准图片
/// </summary>
/// <param name="affineMat"></param>
/// <param name="srcMat"></param>
/// <returns></returns>
private Mat FixImage(Mat affineMat, Mat srcMat)
{
Mat resultMat = new Mat();
Cv2.WarpAffine(srcMat, resultMat, affineMat, srcMat.Size());
return resultMat;
}
/// <summary>
/// 获取映射距阵
/// </summary>
/// <param name="markImage"></param>
/// <param name="srcImage"></param>
/// <returns></returns>
private Mat GetAffineMat(Image markImage, Image srcImage)
{
Mat markMat = ImageUtil.ToMat(new Bitmap(markImage));
Mat originalMat = ImageUtil.ToMat(new Bitmap(srcImage));
Mat srcMat = new Mat();
//灰度图转换
Cv2.CvtColor(markMat, markMat, ColorConversionCodes.RGB2GRAY);
Cv2.CvtColor(originalMat, srcMat, ColorConversionCodes.RGB2GRAY);
//提取特征点
SIFT sift = SIFT.Create(200);
KeyPoint[] markKeyPoints, srcKeyPoints;
MatOfFloat roiDescriptors = new MatOfFloat();
MatOfFloat srcDescriptors = new MatOfFloat();
sift.DetectAndCompute(markMat, null, out markKeyPoints, roiDescriptors);
sift.DetectAndCompute(srcMat, null, out srcKeyPoints, srcDescriptors);
var flannMatcher = new FlannBasedMatcher();
DMatch[] matchePoints = flannMatcher.Match(srcDescriptors, roiDescriptors);
//提取强特征点
double minMatch = 1;
double maxMatch = 0;
for (int i = 0; i < matchePoints.Length; i++)
{
double distance = matchePoints[i].Distance;
//匹配值最大最小值获取
if (distance < minMatch)
{
minMatch = distance;
}
if (distance > maxMatch)
{
maxMatch = distance;
}
}
List<DMatch> goodMatchePoints = new List<DMatch>();
for (int i = 0; i < matchePoints.Length; i++)
{
if (matchePoints[i].Distance < minMatch + (maxMatch - minMatch) / 4)
{
goodMatchePoints.Add(matchePoints[i]);
}
}
//获取排在前N个的最优匹配特征点
int num = goodMatchePoints.Count;
if (num >= 3)
{
num = 3;
}
else
{
//不匹配
return null;
}
List<Point2f> markPoints = new List<Point2f>();
List<Point2f> srcPoints = new List<Point2f>();
goodMatchePoints.Sort((left, right) =>
{
if (left.Distance > right.Distance)
return 1;
else if (left.Distance == right.Distance)
return 0;
else
return -1;
});
//Mat matchMat = new Mat();
//Cv2.DrawMatches(srcMat, srcKeyPoints, markMat, roiKeyPoints, goodMatchePoints.Take(num), matchMat);
//Cv2.ImShow("Match", matchMat);
for (int i = 0; i < num; i++)
{
srcPoints.Add(srcKeyPoints[goodMatchePoints[i].QueryIdx].Pt);
markPoints.Add(markKeyPoints[goodMatchePoints[i].TrainIdx].Pt);
}
//获取图像1到图像2的投影映射矩阵 尺寸为3*3
Mat affineMat = Cv2.GetAffineTransform(srcPoints, markPoints);
return affineMat;
}
}
}