openCvSharp 计算机视觉图片找茬

一、安装包

<PackageReference Include="OpenCvSharp4" Version="4.10.0.20241108" />
<PackageReference Include="OpenCvSharp4.runtime.win" Version="4.10.0.20241108" />

二、准备两张图片

三、编写代码

using OpenCvSharp;
using System;
using System.Diagnostics;
using System.IO;
using static OpenCvSharp.FileStorage;
using static System.Net.Mime.MediaTypeNames;

namespace OpenCvSharpDemo
{
    internal class Program
    {
        static void Main(string[] args)
        {
            Compare();
        }

        static void Compare()
        {
            var path1 = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "Images/A1.png");
            var path2 = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "Images/A2.png");

            // 读取两张图片
            Mat image1 = Cv2.ImRead(path1, ImreadModes.Color);
            Mat image2 = new Mat();
            Cv2.Resize(Cv2.ImRead(path2, ImreadModes.Color), image2, new OpenCvSharp.Size(image1.Size().Width, image1.Size().Height));

            if (image1.Empty() || image2.Empty())
            {
                Console.WriteLine("无法正确读取图片，请检查图片路径是否正确。");
                return;
            }

            // 确保两张图片尺寸一致，如果不一致可以进行调整（这里简单示例假设尺寸相同）
            if (image1.Size() != image2.Size())
            {
                Console.WriteLine("两张图片尺寸不一致，请先处理为相同尺寸。");
                return;
            }

            // 计算两张图片像素差值（逐像素相减）
            Mat diff = new Mat();
            Cv2.Absdiff(image1, image2, diff);

            // 将差异图像转换为灰度图（方便后续阈值处理等操作）
            Mat grayDiff = new Mat();
            Cv2.CvtColor(diff, grayDiff, ColorConversionCodes.BGR2GRAY);

            //膨胀3次
            var kernel = Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(5, 5));
            Cv2.Dilate(grayDiff, grayDiff, kernel, null, 3);

            // 应用阈值，将差异明显的地方凸显出来，这里阈值可以根据实际情况调整
            Mat thresholded = new Mat();
            Cv2.Threshold(grayDiff, thresholded, 30, 255, ThresholdTypes.Binary);

            // 查找轮廓，轮廓所在区域就是不同之处
            Point[][] contours;
            HierarchyIndex[] hierarchy;
            Cv2.FindContours(thresholded, out contours, out hierarchy, RetrievalModes.Tree, ContourApproximationModes.ApproxSimple);

            // 在原始图片（这里选择image1）上绘制出不同之处的轮廓（标记为红色）
            for (int i = 0; i < contours.Length; i++)
            {
                Cv2.DrawContours(image1, contours, i, new Scalar(0, 0, 255), 2);
            }

            // 显示标记出不同之处的图片
            Cv2.ImShow("Differences", image1);
            Cv2.WaitKey(0);
            Cv2.DestroyAllWindows();
         
        }
    }
}

运行：