refactor: 白底/黑底检测算法迁至 BackgroundDefectAnalyzer

- 在 XP.ImageProcessing.Processors 新增静态分析类与 BackgroundDefectMode/BackgroundDefectBlob。

- MainViewModel 仅负责灰度 ROI 提取、坐标平移与 Prism 事件发布。

XP.ImageProcessing.Processors/检测分析/BackgroundDefectAnalyzer.cs

@@ -0,0 +1,102 @@
+// ============================================================================
+// Copyright © 2026 Hexagon Technology Center GmbH. All Rights Reserved.
+// 文件名: BackgroundDefectAnalyzer.cs
+// 描述: 白底/黑底对比下的缺陷斑点分析（仅 ROI 内计算，不接入流水线算子）
+// 算法: Otsu 二值化 → 形态学开运算 → 外轮廓 → 面积过滤 → 外接矩形等效圆
+// 作者: 李伟 wei.lw.li@hexagon.com
+// ============================================================================
+
+using System.Drawing;
+using Emgu.CV;
+using Emgu.CV.CvEnum;
+using Emgu.CV.Structure;
+using Emgu.CV.Util;
+
+namespace XP.ImageProcessing.Processors;
+
+/// <summary>
+/// 底色类型：决定 Otsu 后保留的前景是暗区还是亮区。
+/// </summary>
+public enum BackgroundDefectMode
+{
+    /// <summary>白底图像上检测偏暗区域（BinaryInv + Otsu）。</summary>
+    WhiteBackground,
+
+    /// <summary>黑底图像上检测偏亮区域（Binary + Otsu）。</summary>
+    BlackBackground
+}
+
+/// <summary>
+/// 单个斑点，坐标相对于输入 ROI 左上角；<see cref="SizeMicrometers"/> 与主界面标注逻辑一致（等效直径，微米）。
+/// </summary>
+public readonly record struct BackgroundDefectBlob(Point CenterInRoi, int RadiusPixels, double SizeMicrometers);
+
+/// <summary>
+/// 在灰度 ROI 上执行底色缺陷斑点检测。调用方负责构造与释放 <paramref name="roiGray"/>。
+/// </summary>
+public static class BackgroundDefectAnalyzer
+{
+    /// <summary>
+    /// 在 ROI 灰度图上检测斑点。
+    /// </summary>
+    /// <param name="roiGray">ROI 灰度图（单通道 8 位）。</param>
+    /// <param name="mode">白底或黑底模式。</param>
+    /// <param name="minAreaPixels">轮廓最小面积（像素²），小于此值的轮廓丢弃。</param>
+    /// <param name="mmPerPixel">像素物理尺寸（毫米/像素），用于等效直径换算。</param>
+    /// <param name="morphKernelSize">形态学开运算核尺寸（奇数，默认 3）。</param>
+    public static List<BackgroundDefectBlob> DetectBlobs(
+        Image<Gray, byte> roiGray,
+        BackgroundDefectMode mode,
+        int minAreaPixels = 50,
+        double mmPerPixel = 0.139,
+        int morphKernelSize = 3)
+    {
+        if (roiGray == null) throw new ArgumentNullException(nameof(roiGray));
+        if (minAreaPixels < 1) minAreaPixels = 1;
+        if (mmPerPixel <= 0) mmPerPixel = 0.139;
+        if (morphKernelSize < 1) morphKernelSize = 1;
+        if ((morphKernelSize & 1) == 0) morphKernelSize++;
+
+        int rw = roiGray.Width;
+        int rh = roiGray.Height;
+        if (rw < 1 || rh < 1) return new List<BackgroundDefectBlob>();
+
+        var thresholdType = mode == BackgroundDefectMode.WhiteBackground
+            ? ThresholdType.BinaryInv | ThresholdType.Otsu
+            : ThresholdType.Binary | ThresholdType.Otsu;
+
+        using var binary = new Image<Gray, byte>(rw, rh);
+        CvInvoke.Threshold(roiGray, binary, 0, 255, thresholdType);
+
+        using var kernel = CvInvoke.GetStructuringElement(
+            ElementShape.Ellipse, new Size(morphKernelSize, morphKernelSize), new Point(-1, -1));
+        CvInvoke.MorphologyEx(binary, binary, MorphOp.Open, kernel, new Point(-1, -1), 1,
+            BorderType.Default, new MCvScalar(0));
+
+        using var contours = new VectorOfVectorOfPoint();
+        using var hierarchy = new Mat();
+        CvInvoke.FindContours(binary, contours, hierarchy, RetrType.External, ChainApproxMethod.ChainApproxSimple);
+
+        var result = new List<BackgroundDefectBlob>();
+
+        for (int i = 0; i < contours.Size; i++)
+        {
+            double area = CvInvoke.ContourArea(contours[i]);
+            if (area < minAreaPixels) continue;
+
+            var boundRect = CvInvoke.BoundingRectangle(contours[i]);
+            double radiusF = Math.Max(boundRect.Width, boundRect.Height) / 2.0;
+            var centerF = new PointF(
+                boundRect.X + boundRect.Width / 2.0f,
+                boundRect.Y + boundRect.Height / 2.0f);
+
+            var centerInRoi = new Point((int)centerF.X, (int)centerF.Y);
+            int radiusPx = (int)radiusF;
+            double sizeMicrometers = radiusF * 2.0 * mmPerPixel * 1000.0;
+
+            result.Add(new BackgroundDefectBlob(centerInRoi, radiusPx, sizeMicrometers));
+        }
+
+        return result;
+    }
+}

XplorePlane/ViewModels/Main/MainViewModel.cs

@@ -23,6 +23,7 @@ using XP.Hardware.MotionControl.Abstractions;
 using XP.Hardware.MotionControl.Services;
 using XplorePlane.Events;
 using XplorePlane.Services.MainViewport;
+using XP.ImageProcessing.Processors;
 using XplorePlane.Services.Storage;
 using XplorePlane.ViewModels.Cnc;
 using XplorePlane.Views;
@@ -958,102 +959,8 @@ namespace XplorePlane.ViewModels
             StatusMessage = "白底检测：请在图像上拖拽绘制矩形ROI";
         }
 
-        private void OnWhiteBackgroundRoiDrawn(System.Windows.Int32Rect roi)
-        {
-            try
-            {
-                var viewportVm = _containerProvider.Resolve<ViewportPanelViewModel>();
-                var imageSource = viewportVm?.ImageSource as System.Windows.Media.Imaging.BitmapSource;
-                if (imageSource == null) return;
-
-                // 转为 Gray8
-                System.Windows.Media.Imaging.BitmapSource gray8;
-                if (imageSource.Format != System.Windows.Media.PixelFormats.Gray8)
-                    gray8 = new System.Windows.Media.Imaging.FormatConvertedBitmap(
-                        imageSource, System.Windows.Media.PixelFormats.Gray8, null, 0);
-                else
-                    gray8 = imageSource;
-
-                int imgW = gray8.PixelWidth;
-                int imgH = gray8.PixelHeight;
-
-                // 限制ROI在图像范围内
-                int rx = Math.Clamp(roi.X, 0, imgW - 1);
-                int ry = Math.Clamp(roi.Y, 0, imgH - 1);
-                int rw = Math.Clamp(roi.Width, 1, imgW - rx);
-                int rh = Math.Clamp(roi.Height, 1, imgH - ry);
-
-                // 提取ROI区域像素
-                byte[] roiPixels = new byte[rw * rh];
-                gray8.CopyPixels(new System.Windows.Int32Rect(rx, ry, rw, rh), roiPixels, rw, 0);
-
-                // 使用EmguCV处理
-                using var roiImage = new Emgu.CV.Image<Emgu.CV.Structure.Gray, byte>(rw, rh);
-                for (int y = 0; y < rh; y++)
-                    for (int x = 0; x < rw; x++)
-                        roiImage.Data[y, x, 0] = roiPixels[y * rw + x];
-
-                // Otsu阈值分割（白底检测黑色区域：反转后黑色区域变白）
-                using var binary = new Emgu.CV.Image<Emgu.CV.Structure.Gray, byte>(rw, rh);
-                Emgu.CV.CvInvoke.Threshold(roiImage, binary, 0, 255,
-                    Emgu.CV.CvEnum.ThresholdType.BinaryInv | Emgu.CV.CvEnum.ThresholdType.Otsu);
-
-                // 形态学开运算去噪
-                using var kernel = Emgu.CV.CvInvoke.GetStructuringElement(
-                    Emgu.CV.CvEnum.ElementShape.Ellipse, new System.Drawing.Size(3, 3), new System.Drawing.Point(-1, -1));
-                Emgu.CV.CvInvoke.MorphologyEx(binary, binary,
-                    Emgu.CV.CvEnum.MorphOp.Open, kernel, new System.Drawing.Point(-1, -1), 1,
-                    Emgu.CV.CvEnum.BorderType.Default, new Emgu.CV.Structure.MCvScalar(0));
-
-                // 查找轮廓
-                using var contours = new Emgu.CV.Util.VectorOfVectorOfPoint();
-                using var hierarchy = new Emgu.CV.Mat();
-                Emgu.CV.CvInvoke.FindContours(binary, contours, hierarchy,
-                    Emgu.CV.CvEnum.RetrType.External, Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxSimple);
-
-                // 过滤小区域（最小面积默认50像素²）
-                const int minArea = 50;
-                double pixelSize = 0.139; // mm/pixel，默认值（可从比例尺获取）
-
-                var detections = new System.Collections.Generic.List<(System.Drawing.Point center, int radius, double sizeMm)>();
-
-                for (int i = 0; i < contours.Size; i++)
-                {
-                    double area = Emgu.CV.CvInvoke.ContourArea(contours[i]);
-                    if (area < minArea) continue;
-
-                    // 最小外接圆 - 使用外接矩形计算
-                    var boundRect = Emgu.CV.CvInvoke.BoundingRectangle(contours[i]);
-                    double radiusF = Math.Max(boundRect.Width, boundRect.Height) / 2.0;
-                    var centerF = new System.Drawing.PointF(
-                        boundRect.X + boundRect.Width / 2.0f,
-                        boundRect.Y + boundRect.Height / 2.0f);
-
-                    // 转换到全局坐标
-                    var globalCenter = new System.Drawing.Point((int)centerF.X + rx, (int)centerF.Y + ry);
-                    double diameterMm = radiusF * 2 * pixelSize * 1000; // 转μm
-
-                    detections.Add((globalCenter, (int)radiusF, diameterMm));
-                }
-
-                // 发布结果用于绘制（通过OutputData模式传递给ViewportPanelView）
-                _eventAggregator.GetEvent<WhiteBackgroundResultEvent>().Publish(
-                    new WhiteBackgroundResultPayload
-                    {
-                        RoiRect = new System.Drawing.Rectangle(rx, ry, rw, rh),
-                        Detections = detections
-                    });
-
-                StatusMessage = $"白底检测完成：检测到 {detections.Count} 个黑色区域";
-                _logger.Info("White background detection: found {Count} dark regions in ROI ({X},{Y},{W},{H})",
-                    detections.Count, rx, ry, rw, rh);
-            }
-            catch (Exception ex)
-            {
-                _logger.Error(ex, "White background detection failed");
-                StatusMessage = $"白底检测失败: {ex.Message}";
-            }
-        }
+        private void OnWhiteBackgroundRoiDrawn(System.Windows.Int32Rect roi) =>
+            RunBackgroundRoiDetection(roi, BackgroundDefectMode.WhiteBackground);
 
         private void ExecuteBlackBackgroundDetection()
         {
@@ -1063,7 +970,13 @@ namespace XplorePlane.ViewModels
             StatusMessage = "黑底检测：请在图像上拖拽绘制矩形ROI";
         }
 
-        private void OnBlackBackgroundRoiDrawn(System.Windows.Int32Rect roi)
+        private void OnBlackBackgroundRoiDrawn(System.Windows.Int32Rect roi) =>
+            RunBackgroundRoiDetection(roi, BackgroundDefectMode.BlackBackground);
+
+        /// <summary>
+        /// 从视口灰度图取 ROI，调用 <see cref="BackgroundDefectAnalyzer"/>，再发布结果事件（全局坐标）。
+        /// </summary>
+        private void RunBackgroundRoiDetection(System.Windows.Int32Rect roi, BackgroundDefectMode mode)
         {
             try
             {
@@ -1089,64 +1002,45 @@ namespace XplorePlane.ViewModels
                 byte[] roiPixels = new byte[rw * rh];
                 gray8.CopyPixels(new System.Windows.Int32Rect(rx, ry, rw, rh), roiPixels, rw, 0);
 
-                using var roiImage = new Emgu.CV.Image<Emgu.CV.Structure.Gray, byte>(rw, rh);
+                using var roiImage = new Image<Gray, byte>(rw, rh);
                 for (int y = 0; y < rh; y++)
                     for (int x = 0; x < rw; x++)
                         roiImage.Data[y, x, 0] = roiPixels[y * rw + x];
 
-                // Otsu 二值化（黑底检测亮色区域：高于阈值为前景）
-                using var binary = new Emgu.CV.Image<Emgu.CV.Structure.Gray, byte>(rw, rh);
-                Emgu.CV.CvInvoke.Threshold(roiImage, binary, 0, 255,
-                    Emgu.CV.CvEnum.ThresholdType.Binary | Emgu.CV.CvEnum.ThresholdType.Otsu);
-
-                using var kernel = Emgu.CV.CvInvoke.GetStructuringElement(
-                    Emgu.CV.CvEnum.ElementShape.Ellipse, new System.Drawing.Size(3, 3), new System.Drawing.Point(-1, -1));
-                Emgu.CV.CvInvoke.MorphologyEx(binary, binary,
-                    Emgu.CV.CvEnum.MorphOp.Open, kernel, new System.Drawing.Point(-1, -1), 1,
-                    Emgu.CV.CvEnum.BorderType.Default, new Emgu.CV.Structure.MCvScalar(0));
-
-                using var contours = new Emgu.CV.Util.VectorOfVectorOfPoint();
-                using var hierarchy = new Emgu.CV.Mat();
-                Emgu.CV.CvInvoke.FindContours(binary, contours, hierarchy,
-                    Emgu.CV.CvEnum.RetrType.External, Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxSimple);
-
                 const int minArea = 50;
-                double pixelSize = 0.139;
+                const double mmPerPixel = 0.139;
+                var blobs = BackgroundDefectAnalyzer.DetectBlobs(roiImage, mode, minArea, mmPerPixel);
 
-                var detections = new System.Collections.Generic.List<(System.Drawing.Point center, int radius, double sizeMm)>();
-
-                for (int i = 0; i < contours.Size; i++)
+                var detections = new System.Collections.Generic.List<(System.Drawing.Point center, int radius, double sizeMm)>(blobs.Count);
+                foreach (var b in blobs)
                 {
-                    double area = Emgu.CV.CvInvoke.ContourArea(contours[i]);
-                    if (area < minArea) continue;
-
-                    var boundRect = Emgu.CV.CvInvoke.BoundingRectangle(contours[i]);
-                    double radiusF = Math.Max(boundRect.Width, boundRect.Height) / 2.0;
-                    var centerF = new System.Drawing.PointF(
-                        boundRect.X + boundRect.Width / 2.0f,
-                        boundRect.Y + boundRect.Height / 2.0f);
-
-                    var globalCenter = new System.Drawing.Point((int)centerF.X + rx, (int)centerF.Y + ry);
-                    double diameterMm = radiusF * 2 * pixelSize * 1000;
-
-                    detections.Add((globalCenter, (int)radiusF, diameterMm));
+                    var globalCenter = new System.Drawing.Point(b.CenterInRoi.X + rx, b.CenterInRoi.Y + ry);
+                    detections.Add((globalCenter, b.RadiusPixels, b.SizeMicrometers));
                 }
 
-                _eventAggregator.GetEvent<BlackBackgroundResultEvent>().Publish(
-                    new BlackBackgroundResultPayload
-                    {
-                        RoiRect = new System.Drawing.Rectangle(rx, ry, rw, rh),
-                        Detections = detections
-                    });
-
-                StatusMessage = $"黑底检测完成：检测到 {detections.Count} 个亮色区域";
-                _logger.Info("Black background detection: found {Count} bright regions in ROI ({X},{Y},{W},{H})",
-                    detections.Count, rx, ry, rw, rh);
+                var roiRect = new System.Drawing.Rectangle(rx, ry, rw, rh);
+                if (mode == BackgroundDefectMode.WhiteBackground)
+                {
+                    _eventAggregator.GetEvent<WhiteBackgroundResultEvent>().Publish(
+                        new WhiteBackgroundResultPayload { RoiRect = roiRect, Detections = detections });
+                    StatusMessage = $"白底检测完成：检测到 {detections.Count} 个黑色区域";
+                    _logger.Info("White background detection: found {Count} dark regions in ROI ({X},{Y},{W},{H})",
+                        detections.Count, rx, ry, rw, rh);
+                }
+                else
+                {
+                    _eventAggregator.GetEvent<BlackBackgroundResultEvent>().Publish(
+                        new BlackBackgroundResultPayload { RoiRect = roiRect, Detections = detections });
+                    StatusMessage = $"黑底检测完成：检测到 {detections.Count} 个亮色区域";
+                    _logger.Info("Black background detection: found {Count} bright regions in ROI ({X},{Y},{W},{H})",
+                        detections.Count, rx, ry, rw, rh);
+                }
             }
             catch (Exception ex)
             {
-                _logger.Error(ex, "Black background detection failed");
-                StatusMessage = $"黑底检测失败: {ex.Message}";
+                string label = mode == BackgroundDefectMode.WhiteBackground ? "白底" : "黑底";
+                _logger.Error(ex, "{Label} background detection failed", label);
+                StatusMessage = $"{label}检测失败: {ex.Message}";
             }
         }