using System;
using System.Collections.Generic;
using System.Drawing;
using
Emgu.CV;
using
Emgu.CV.CvEnum;
using
Emgu.CV.Structure;
using MathNet.Numerics;
namespace ImageProcessingExample
{
class Program
{
static void Main
(string[] args
)
{
// 读取图像
Image<Bgr, byte> originalImage
= new Image<Bgr, byte>
("path_to_your_image.jpg"
);
// 图像金字塔预处理
List<Image<Bgr, byte>> imagePyramid
= GenerateImagePyramid
(originalImage, 3
);
// 取金字塔中的某一层进行后续处理，这里取最后一层
Image<Bgr, byte> processedImage
= imagePyramid[imagePyramid.Count - 1];
// 假设我们已经有了一些目标点的坐标，这里
简单模拟
List<Point> targetPoints
= new List<Point>
();
Random random
= new Random
();
for
(int i
= 0; i < 10; i++
)
{
targetPoints.Add
(new Point
(random.Next
(processedImage.
Width), random.Next
(processedImage.
Height)));
}
// 使用DBSCAN聚类
List<List<Point>> clusters
= DBSCANClustering
(targetPoints, 10, 3
);
// 在图像上绘制正方形框选目标
DrawBoundingBoxes
(processedImage, clusters
);
// 显示处理后的图像
CvInvoke.Imshow
("Processed Image", processedImage
);
CvInvoke.WaitKey
(0
);
}
static List<Image<Bgr, byte>> GenerateImagePyramid
(Image<Bgr, byte> originalImage, int levels
)
{
List<Image<Bgr, byte>> pyramid
= new List<Image<Bgr, byte>>
();
pyramid.Add
(originalImage
);
for
(int i
= 1; i < levels; i++
)
{
Image<Bgr, byte> downsampledImage
= pyramid[i - 1].PyrDown
();
pyramid.Add
(downsampledImage
);
}
return pyramid;
}
static List<List<Point>> DBSCANClustering
(List<Point> points,
double eps, int minPts
)
{
var data
= new double[points.Count, 2];
for
(int i
= 0; i < points.Count; i++
)
{
data[i, 0]
= points[i].X;
data[i, 1]
= points[i].Y;
}
var dbscan
= new DBSCAN
();
var clusters
= dbscan.Train
(data, eps, minPts
);
List<List<Point>> result
= new List<List<Point>>
();
for
(int i
= 0; i < clusters.Length; i++
)
{
List<Point> clusterPoints
= new List<Point>
();
for
(int j
= 0; j < clusters[i].Length; j++
)
{
if
(clusters[i][j]
)
{
clusterPoints.Add
(points[j]
);
}
}
if
(clusterPoints.Count > 0
)
{
result.Add
(clusterPoints
);
}
}
return result;
}
static void DrawBoundingBoxes
(Image<Bgr, byte> image, List<List<Point>> clusters
)
{
foreach
(var cluster in clusters
)
{
int minX
= int.MaxValue;
int minY
= int.MaxValue;
int maxX
= int.MinValue;
int maxY
= int.MinValue;
foreach
(var point in cluster
)
{
if
(point.X < minX
) minX
= point.X;
if
(point.X > maxX
) maxX
= point.X;
if
(point.Y < minY
) minY
= point.Y;
if
(point.Y > maxY
) maxY
= point.Y;
}
Rectangle boundingBox
= new Rectangle
(minX, minY, maxX - minX, maxY - minY
);
image.Draw
(boundingBox,
new Bgr
(Color.Red
), 2
);
}
}
}
}
中报错DBSCAN
本文介绍了一个简单的矩阵创建及元素赋值方法，并展示了如何通过特定组件显示该矩阵。使用了Matrix<Double>类创建一个5x7的矩阵，并通过双重循环为每个元素赋值。
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