OpenCvSharp是OpenCV库的C#封装，提供了丰富的图像处理功能。模板匹配是一种在大图像中查找小模板图像位置的技术。在这篇文章中，我们将介绍如何使用OpenCvSharp进行模板匹配，并考虑目标尺寸大小的匹配。

以下是实现模板匹配的详细步骤：

1. 安装 OpenCvSharp
2. 加载图像和模板
3. 进行模板匹配
4. 计算匹配结果的尺寸
5. 在接受范围内绘制匹配结果

安装 OpenCvSharp

你可以通过NuGet包管理器来安装OpenCvSharp。运行以下命令：

Bash
Install-Package OpenCvSharp4
Install-Package OpenCvSharp4.runtime.win

实例一

加载图像和模板

目标图

模板

首先，我们需要加载包含目标图像和模板图像的文件。

代码

C#
using OpenCvSharp;

namespace App1
{
    internal class Program
    {
        static void Main(string[] args)
        {
            // 读取待搜索的大图和模板小图
            Mat targetImage = Cv2.ImRead("pcb_layout.png", ImreadModes.Color);
            Mat templateImage = Cv2.ImRead("template.png", ImreadModes.Color);

            // 确保图片正确加载
            if (targetImage.Empty() || templateImage.Empty())
            {
                Console.WriteLine("图像加载失败！");
                return;
            }
            // 运行模板匹配
            Mat result = new Mat();
            Cv2.MatchTemplate(targetImage, templateImage, result, TemplateMatchModes.CCoeffNormed);

            // 设定匹配结果的阈值
            double threshold = 0.8;

            // 找到所有匹配度高于阈值的匹配结果
            List<Rect> matches = new List<Rect>();
            for (int y = 0; y < result.Rows; y++)
            {
                for (int x = 0; x < result.Cols; x++)
                {
                    if (result.At<float>(y, x) >= threshold)
                    {
                        Rect matchRect = new Rect(new Point(x, y), new Size(templateImage.Width, templateImage.Height));
                        matches.Add(matchRect);
                    }
                }
            }

            // 计算匹配结果的尺寸并筛选有效匹配
            List<Rect> validMatches = new List<Rect>();
            foreach (var matchRect in matches)
            {
                double matchWidth = matchRect.Width;
                double matchHeight = matchRect.Height;
                double templateWidth = templateImage.Width;
                double templateHeight = templateImage.Height;

                double widthRatio = matchWidth / templateWidth;
                double heightRatio = matchHeight / templateHeight;

                bool isAcceptableMatch = widthRatio <= 1.2 && widthRatio >= 0.8 && heightRatio <= 1.2 && heightRatio >= 0.8;

                if (isAcceptableMatch)
                {
                    validMatches.Add(matchRect);
                }
            }

            // 去除相互重叠的匹配结果
            List<Rect> nonOverlappingMatches = FilterOverlappingMatches(validMatches);

            // 在目标图像上绘制矩形框以标注匹配区域
            foreach (var match in nonOverlappingMatches)
            {
                Cv2.Rectangle(targetImage, match, Scalar.Red, 2);
            }

            Console.WriteLine($"{nonOverlappingMatches.Count} 个匹配找到！");
            Cv2.ImShow("Matched Image", targetImage);
            Cv2.WaitKey(0);
        }

        // 函数用于去除重叠的匹配结果
        static List<Rect> FilterOverlappingMatches(List<Rect> matches, double minOverlapRatio = 0.5)
        {
            List<Rect> filteredMatches = new List<Rect>();

            foreach (var match in matches)
            {
                bool overlap = false;
                foreach (var filteredMatch in filteredMatches)
                {
                    Rect intersection = match & filteredMatch;
                    double intersectionArea = intersection.Width * intersection.Height;
                    double matchArea = match.Width * match.Height;
                    double filteredMatchArea = filteredMatch.Width * filteredMatch.Height;
                    double overlapRatio = intersectionArea / Math.Min(matchArea, filteredMatchArea);
                    if (overlapRatio > minOverlapRatio)
                    {
                        overlap = true;
                        break;
                    }
                }
                if (!overlap)
                {
                    filteredMatches.Add(match);
                }
            }

            return filteredMatches;
        }

    }
}

计算匹配结果尺寸并筛选有效的匹配。这里比较的是匹配区域与模板区域的宽高比，确保在接受的范围内（0.8到1.2之间）。

输出结果