OpenCv案例(八)：基于OpenCVSharp学习之模板匹配

1：建好测试Demo

C#项目中添加好OpenCVSharp安装包如下图（图中是VS2015版本）
NuGet工具给项目添加OpenCvSharp3-AnyCPU：
工具>>NuGet包管理器>>管理解决方案的NuGet程序包

2：测试Demo

首先，添加引用：using OpenCvSharp;
其次，添加如下函数代码代码段

对模板匹配方法使用前的准备

 /// <summary>
        /// 模板匹配  
        /// </summary>
        /// <param name="srcImg">被匹配图像路径</param>
        /// <param name="tempImg">模板图像路径</param>
        /// <returns>当前匹配完成后 模板在匹配图像中左上角的坐标点</returns>
        public OpenCvSharp.Point TemplateMatch(string srcImg, string tempImg, out double matchVal)
        {
            OpenCvSharp.Point tempPoint = new OpenCvSharp.Point();
            Mat srcImage = Cv2.ImRead(srcImg, ImreadModes.Grayscale);
            Mat tempImage = Cv2.ImRead(tempImg, ImreadModes.Grayscale);
            Bitmap bmp = MatchTemplate(tempImage, srcImage, out tempPoint, out matchVal);
            //保存图像路径
            bmp.Save(System.AppDomain.CurrentDomain.BaseDirectory + @"ImgFile\processedImg" + DateTime.Now.ToString("yyMMddHHmmss") + ".bmp");
            return tempPoint;
        }

模板匹配方法

/// <summary>
/// 模板匹配
/// </summary>
/// <param name="tempalte">模板图片像</param>
/// <param name="srcPic">被匹配图像</param>
/// <param name="tempPoint">返回模板图像在匹配图像中的坐标位置</param>
/// <returns>标注匹配区域的图像</returns> 
private Bitmap MatchTemplate(Mat tempalte, Mat srcPic, out OpenCvSharp.Point tempPoint, out double matchValue)
        {
            Mat result = new Mat(); 
            //模板匹配
            Cv2.MatchTemplate(srcPic, tempalte, result, TemplateMatchModes.CCoeffNormed);//CCoeffNormed  最好匹配为1,值越小匹配越差
            Double minVul;
            Double maxVul;
            OpenCvSharp.Point minLoc = new OpenCvSharp.Point(0, 0);
            OpenCvSharp.Point maxLoc = new OpenCvSharp.Point(0, 0);
            OpenCvSharp.Point matchLoc = new OpenCvSharp.Point(0, 0);
            //归一化
            Cv2.Normalize(result, result, 0, 1, NormTypes.MinMax, -1);
            //寻找极值
            Cv2.MinMaxLoc(result, out minVul, out maxVul, out minLoc, out maxLoc);
            //最大值坐标
            matchLoc = maxLoc;
            Mat mask = srcPic.Clone();//复制整个矩阵
            //画框显示 :对角线画框，起点和终点，都用Point，线宽
            Cv2.Rectangle(mask, matchLoc, new OpenCvSharp.Point(matchLoc.X + tempalte.Cols, matchLoc.Y + tempalte.Rows), Scalar.Green, 2);//2代表画的线条的宽细程度

            //Console.WriteLine("最大值：{0}，X:{1}，Y:{2}", maxVul, matchLoc.Y, matchLoc.X);
            matchValue = maxVul;
            tempPoint.X = matchLoc.X;
            tempPoint.Y = matchLoc.Y;
            //循环查找画框显示
            Double threshold = 0.91;
            Mat maskMulti = srcPic.Clone();
            for (int i = 1; i < result.Rows - tempalte.Rows; i += tempalte.Rows)
            {
                for (int j = 1; j < result.Cols - tempalte.Cols; j += tempalte.Cols)
                {
                    Rect roi = new Rect(j, i, tempalte.Cols, tempalte.Rows);        //建立感兴趣
                    Mat RoiResult = new Mat(result, roi);
                    Cv2.MinMaxLoc(RoiResult, out minVul, out maxVul, out minLoc, out maxLoc);//查找极值
                    matchLoc = maxLoc;//最大值坐标
                    if (maxVul > threshold)
                    {
                        //画框显示
                        Cv2.Rectangle(maskMulti, new OpenCvSharp.Point(j + maxLoc.X, i + maxLoc.Y), new OpenCvSharp.Point(j + maxLoc.X + tempalte.Cols, i + maxLoc.Y + tempalte.Rows), Scalar.Green, 2);
                        string axis = '(' + Convert.ToString(i + maxLoc.Y) + ',' + Convert.ToString(j + maxLoc.X) + ')';
                        Cv2.PutText(maskMulti, axis, new OpenCvSharp.Point(j + maxLoc.X, i + maxLoc.Y), HersheyFonts.HersheyPlain, 1, Scalar.Red, 1, LineTypes.Link4);
                    }
                }
            }
            //返回匹配后图像
            return OpenCvSharp.Extensions.BitmapConverter.ToBitmap(mask);
        }

3：测试结果

被匹配图像
模板图像
匹配结果
效果可以滴，但是经过多次不同程度实验结果表明，误差还是有的

3：学习资料

OpenCv中文网站：OpenCV中文网站-论坛 - Powered by Discuz!
OpenCV官方教程 -Template Matching：OpenCV模板匹配_w3cschool

OpenCv案例(八)：基于OpenCVSharp学习之模板匹配

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