c#中WinForm用OpencvSharp实现ROI区域提取的示例

2024-04-02 19:55

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已经自学OpencvSharp一段时间了(目前工作用的是C#，就学了Opencvsharp了,vs2015，opencvsharp3)，收获也有一些，现在就将我在学习过程中的收获分享出来吧。

图像处理，很常见的问题，但对于大多数时候而言，我们往往不需要去处理整张图片，而是只需要处理一部分，这就涉及到了ROI(Region of interest)的提取了。我目前提取ROI的方法是采用掩膜Mask的方法。具体的思路就是：在图像操作的时候，定义一张同等大小的空的Mask，也就是全部是0，然后将我们想要的ROI轮廓画在Mask上，并填充内部，就会得到新的Mask，这个新的Mask就只有在ROI区域非0，其余地方元素都是0，再把用Cv2.BoundingRect()将包含ROI区域的轮廓的最小矩形找出来，分别将原图与Mask这两幅图像的这个最小矩形部分提出来，最后再调用Cv2.BitwiseAnd()这个方法，通常情况而言，一副图像与自己本身进行与运算,输出的还是本身图像，带上掩膜Mask后，就只会输出图像在Mask非0区域部分(也就是我们所需要的ROI)的图像了，这样就实现了我们的ROI提取了。

接下来，就分享几种常见ROI区域提取吧。

部分代码如下：

主要使用的变量

         /// 放在yVars.ImgOptions中 
   public struct ROIMatt   
            {
                public static string Image;//原图  
                public static bool IsSelectRegion = false;
 
                public static int step; //ROI区域移动步长
                public static int angel; // 旋转一次 angel±=step; 旋转角度 
 
                public static yDirections direct = yDirections.NULL;
                public static yROIRegionType ROIType = yROIRegionType.Rectangle;
 
                // 矩形ROI
                // 矩形四个点坐标 都是相对于图像的坐标 而不是相对于picturebox的坐标
                // 矩形四个点相对位置 刚开始确定矩形时就这样 经过旋转后位置变 但相对位置还是这样
                //  1  2      // 按顺时针数的点   1-->2-->4-->3-->1-->2-->4-->3-->1
                //  3  4
                public static OpenCvSharp.Point rectFirstPoint = new OpenCvSharp.Point();
                public static OpenCvSharp.Point rectSecondPoint = new OpenCvSharp.Point();
                public static OpenCvSharp.Point rectThirdPoint = new OpenCvSharp.Point();
                public static OpenCvSharp.Point rectFourthPoint = new OpenCvSharp.Point(); 
                public static double rectWidth = 0;
                public static double rectHeight = 0;
 
                // 圆形ROI
                public static OpenCvSharp.Point cirCenter = new OpenCvSharp.Point(0.0,0.0); // 圆心
                public static int cirRadious = 0; // 半径
                // 椭圆ROI
                public static OpenCvSharp.Point elpCenter = new OpenCvSharp.Point(0.0,0.0); // 椭圆中心点
                public static double elpAngel = 0.0;//椭圆倾斜角度
                public static double elpLongAxis = 0.0; // 长轴
                public static double elpShortAxis = 0.0; // 短轴
            }

我的picturebox的SizeMode是StretchImage的，可能看起来跟想要的结果有点差异，但是实际上是一样的。

首先是最常见的矩形。

对于正矩形而言，我们可以直接定义出图像的ROI区域

public Mat(Mat m, Rect roi);

这样定义的图像就是原图m的指定区域了。但对于倾斜的矩阵，RotatedRect，而言，就得需要使用掩膜了，提取ROI的方法以及结果如下：

        public static void ImgMattingRect()
        {
            Mat pic = new Mat(yVars.ImgOptions.ROIMatt.Image);
            Mat mask = Mat.Zeros(pic.Size(), MatType.CV_8UC1);
            OpenCvSharp.Point2f[] coutours = new OpenCvSharp.Point2f[4];
            coutours[0] = yVars.ImgOptions.ROIMatt.rectFirstPoint;
            coutours[1] = yVars.ImgOptions.ROIMatt.rectSecondPoint;
            coutours[2] = yVars.ImgOptions.ROIMatt.rectFourthPoint;
            coutours[3] = yVars.ImgOptions.ROIMatt.rectThirdPoint;
 
            List<OpenCvSharp.Point> listt = new List<OpenCvSharp.Point>();
            for (int i = 0; i < coutours.Count(); i++)
            {
                listt.Add(new OpenCvSharp.Point(coutours[i].X, coutours[i].Y));
            }
 
            List<List<OpenCvSharp.Point>> pp = new List<List<OpenCvSharp.Point>>() { listt };
 
            Cv2.FillPoly(mask, pp, new Scalar(255, 255, 255)); 
            OpenCvSharp.Rect rect = Cv2.BoundingRect(coutours);
            Mat class="lazy" data-src = new Mat(pic, rect);
            Mat maskROI = new Mat(mask, rect);
            Mat picOut = new Mat();
            Cv2.BitwiseAnd(class="lazy" data-src, class="lazy" data-src, picOut, maskROI);
            Form1.Instance.pbxMattImage.Image = yImgConvert.MatToBitmap(picOut);
 
            yVars.ImgOptions.ROIMatt.rectFirstPoint = new OpenCvSharp.Point(0, 0);
            yVars.ImgOptions.ROIMatt.rectSecondPoint = new OpenCvSharp.Point(0, 0);
            yVars.ImgOptions.ROIMatt.rectThirdPoint = new OpenCvSharp.Point(0, 0);
            yVars.ImgOptions.ROIMatt.rectFourthPoint = new OpenCvSharp.Point(0, 0);
        }

缩放平移和旋转就只要改变矩形的四个顶点坐标就行了。方法都一样就不赘述了。

圆形ROI区域,

方法如下：

        public static void ImgMattingCircle()
        {
            Mat mm = new Mat(yVars.ImgOptions.ROIMatt.Image);
            Mat mask = Mat.Zeros(mm.Size(), MatType.CV_8UC3);
 
            Cv2.Circle(mask, yVars.ImgOptions.ROIMatt.cirCenter, yVars.ImgOptions.ROIMatt.cirRadious, Scalar.Red, 1, LineTypes.AntiAlias);
            Cv2.FloodFill(mask, yVars.ImgOptions.ROIMatt.cirCenter, Scalar.Red);
 
            mask.ConvertTo(mask, MatType.CV_8UC1);
 
            int xx = yVars.ImgOptions.ROIMatt.cirCenter.X - yVars.ImgOptions.ROIMatt.cirRadious;
            int yy = yVars.ImgOptions.ROIMatt.cirCenter.Y - yVars.ImgOptions.ROIMatt.cirRadious;
            int rr = 2 * yVars.ImgOptions.ROIMatt.cirRadious;
            // 圆的外接正方形
            Rect rect = new Rect(new OpenCvSharp.Point(xx, yy), new OpenCvSharp.Size(rr, rr));
 
            Mat class="lazy" data-src = new Mat(mm, rect);
            Mat maskRoI = new Mat(mask, rect);
 
            Cv2.CvtColor(maskRoI, maskRoI, ColorConversionCodes.BGR2GRAY);
 
            Mat picOut = new Mat();
            Cv2.BitwiseAnd(class="lazy" data-src, class="lazy" data-src, picOut, maskRoI);
 
            Form1.Instance.pbxMattImage.Image = yImgConvert.MatToBitmap(picOut);
 
            yVars.ImgOptions.ROIMatt.cirCenter = new OpenCvSharp.Point(0, 0);
            yVars.ImgOptions.ROIMatt.cirRadious = 0;
        }

效果展示:

圆形ROI的移动时就只有圆心坐标变半径不变，而缩放时只改变半径，圆心不变，注意移动时别超出图像界限就行。

椭圆ROI

在Opencvsharp中绘制椭圆有两种方式

        //
        // 摘要:
        //     Draws simple or thick elliptic arc or fills ellipse sector
        //
        // 参数:
        //   img:
        //     Image.
        //
        //   box:
        //     The enclosing box of the ellipse drawn
        //
        //   color:
        //     Ellipse color.
        //
        //   thickness:
        //     Thickness of the ellipse boundary. [By default this is 1]
        //
        //   lineType:
        //     Type of the ellipse boundary. [By default this is LineType.Link8]
        public static void Ellipse(InputOutputArray img, RotatedRect box, Scalar color, int thickness = 1, LineTypes lineType = LineTypes.Link8);
        //
        // 摘要:
        //     Draws simple or thick elliptic arc or fills ellipse sector
        //
        // 参数:
        //   img:
        //     Image.
        //
        //   center:
        //     Center of the ellipse.
        //
        //   axes:
        //     Length of the ellipse axes.
        //
        //   angle:
        //     Rotation angle.
        //
        //   startAngle:
        //     Starting angle of the elliptic arc.
        //
        //   endAngle:
        //     Ending angle of the elliptic arc.
        //
        //   color:
        //     Ellipse color.
        //
        //   thickness:
        //     Thickness of the ellipse arc. [By default this is 1]
        //
        //   lineType:
        //     Type of the ellipse boundary. [By default this is LineType.Link8]
        //
        //   shift:
        //     Number of fractional bits in the center coordinates and axes' values. [By default
        //     this is 0]
        public static void Ellipse(InputOutputArray img, Point center, Size axes, double angle, double startAngle, double endAngle, Scalar color, int thickness = 1, LineTypes lineType = LineTypes.Link8, int shift = 0);

我们采用第一种方式，即可以将椭圆转化成一个RotatedRect，只要在画RotatedRect的时候改成画椭圆即可，就可以回到第一种矩形的ROI提取上面了，代码如下：

        public static void ImgMattingEllipse()
        {
            Mat mm = new Mat(yVars.ImgOptions.ROIMatt.Image);
            Mat mask = Mat.Zeros(mm.Size(), MatType.CV_8UC3);
 
            RotatedRect rorect = new RotatedRect(yVars.ImgOptions.ROIMatt.elpCenter, new Size2f(yVars.ImgOptions.ROIMatt.elpLongAxis, yVars.ImgOptions.ROIMatt.elpShortAxis), (float)yVars.ImgOptions.ROIMatt.elpAngel);
            Cv2.Ellipse(mask, rorect, Scalar.Red);
 
            Mat gray = new Mat();
            Cv2.CvtColor(mask, gray, ColorConversionCodes.BGR2GRAY);
            Cv2.Threshold(gray, gray, 100, 255, ThresholdTypes.Otsu);
 
            OpenCvSharp.Point[][] contours;
            HierarchyIndex[] hierarchly;
            Cv2.FindContours(gray, out contours, out hierarchly, RetrievalModes.Tree, ContourApproximationModes.ApproxSimple, new OpenCvSharp.Point(0, 0));
 
            Rect rect = Cv2.BoundingRect(contours[0]);
 
            Cv2.FloodFill(mask, yVars.ImgOptions.ROIMatt.elpCenter, Scalar.Red);
 
            mask.ConvertTo(mask, MatType.CV_8UC1);
 
            Mat class="lazy" data-src = new Mat(mm, rect);
            Mat maskRoI = new Mat(mask, rect);
            Cv2.CvtColor(maskRoI, maskRoI, ColorConversionCodes.BGR2GRAY);
            Mat picOut = new Mat();
            Cv2.BitwiseAnd(class="lazy" data-src, class="lazy" data-src, picOut, maskRoI);
 
            Form1.Instance.pbxMattImage.Image = yImgConvert.MatToBitmap(picOut);
        }

实验结果如下：