C# 如何在一张大图片中快速找到另外一张图片（两种方式）？
自己写了一种，速度不是很快，但是能够实现
var findpic = new FindPic(); var rec = findpic.FindPicture(@"C:\Users\zaranet\Desktop\xiao.png", @"C:\Users\zaranet\Desktop\da.png", 10); MessageBox.Show(rec[0].X +","+rec[0].Y);
Find类，在这其中先删除了最外边界的高宽，最后注意循环足够rate则直接返回。
class FindPic { #region 找图 /// <summary> /// 查找图片，不能镂空 /// </summary> /// <param name="subPic">要查找坐标的小图</param> /// <param name="parPic">在哪个大图里查找</param> /// <param name="errorRange">容错，单个色值范围内视为正确0~255</param> /// <param name="searchRect">如果为empty，则默认查找整个图像</param> /// <param name="matchRate">图片匹配度，默认90%</param> /// <param name="isFindAll">是否查找所有相似的图片</param> /// <returns>返回查找到的图片的中心点坐标</returns> public List<System.Drawing.Point> FindPicture(string subPic, string parPic, byte errorRange = 0, Rectangle searchRect = new System.Drawing.Rectangle(), double matchRate = 0.9, bool isFindAll = false) { List<System.Drawing.Point> ListPoint = new List<System.Drawing.Point>(); var subBitmap = new Bitmap(subPic); var parBitmap = new Bitmap(parPic); int subWidth = subBitmap.Width; int subHeight = subBitmap.Height; int parWidth = parBitmap.Width; int parHeight = parBitmap.Height; if (searchRect.IsEmpty) { searchRect = new Rectangle(0, 0, parBitmap.Width, parBitmap.Height); } var searchLeftTop = searchRect.Location; var searchSize = searchRect.Size; System.Drawing.Color startPixelColor = subBitmap.GetPixel(0, 0); var subData = subBitmap.LockBits(new Rectangle(0, 0, subBitmap.Width, subBitmap.Height), ImageLockMode.ReadOnly, System.Drawing.Imaging.PixelFormat.Format32bppArgb); var parData = parBitmap.LockBits(new Rectangle(0, 0, parBitmap.Width, parBitmap.Height), ImageLockMode.ReadOnly, System.Drawing.Imaging.PixelFormat.Format32bppArgb); var byteArrarySub = new byte[subData.Stride * subData.Height]; var byteArraryPar = new byte[parData.Stride * parData.Height]; Marshal.Copy(subData.Scan0, byteArrarySub, 0, subData.Stride * subData.Height); Marshal.Copy(parData.Scan0, byteArraryPar, 0, parData.Stride * parData.Height); var iMax = searchLeftTop.Y + searchSize.Height - subData.Height;//行 var jMax = searchLeftTop.X + searchSize.Width - subData.Width;//列 int smallOffsetX = 0, smallOffsetY = 0; int smallStartX = 0, smallStartY = 0; int pointX = -1; int pointY = -1; for (int i = searchLeftTop.Y; i < iMax; i++) { for (int j = searchLeftTop.X; j < jMax; j++) { //大图x，y坐标处的颜色值 int x = j, y = i; int parIndex = i * parWidth * 4 + j * 4; var colorBig = System.Drawing.Color.FromArgb(byteArraryPar[parIndex + 3], byteArraryPar[parIndex + 2], byteArraryPar[parIndex + 1], byteArraryPar[parIndex]); ; if (ColorAEqualColorB(colorBig, startPixelColor, errorRange)) { smallStartX = x - smallOffsetX;//待找的图X坐标 smallStartY = y - smallOffsetY;//待找的图Y坐标 int sum = 0;//所有需要比对的有效点 int matchNum = 0;//成功匹配的点 for (int m = 0; m < subHeight; m++) { for (int n = 0; n < subWidth; n++) { int x1 = n, y1 = m; int subIndex = m * subWidth * 4 + n * 4; var color = System.Drawing.Color.FromArgb(byteArrarySub[subIndex + 3], byteArrarySub[subIndex + 2], byteArrarySub[subIndex + 1], byteArrarySub[subIndex]); sum++; int x2 = smallStartX + x1, y2 = smallStartY + y1; int parReleativeIndex = y2 * parWidth * 4 + x2 * 4;//比对大图对应的像素点的颜色 var colorPixel = System.Drawing.Color.FromArgb(byteArraryPar[parReleativeIndex + 3], byteArraryPar[parReleativeIndex + 2], byteArraryPar[parReleativeIndex + 1], byteArraryPar[parReleativeIndex]); if (ColorAEqualColorB(colorPixel, color, errorRange)) { matchNum++; } } } if ((double)matchNum / sum >= matchRate) { Console.WriteLine((double)matchNum / sum); pointX = smallStartX + (int)(subWidth / 2.0); pointY = smallStartY + (int)(subHeight / 2.0); var point = new System.Drawing.Point(pointX, pointY); if (!ListContainsPoint(ListPoint, point, 10)) { ListPoint.Add(point); } if (!isFindAll) { goto FIND_END; } } } //小图x1,y1坐标处的颜色值 } } FIND_END: subBitmap.UnlockBits(subData); parBitmap.UnlockBits(parData); subBitmap.Dispose(); parBitmap.Dispose(); GC.Collect(); return ListPoint; } #endregion public bool ColorAEqualColorB(System.Drawing.Color colorA, System.Drawing.Color colorB, byte errorRange = 10) { return colorA.A <= colorB.A + errorRange && colorA.A >= colorB.A - errorRange && colorA.R <= colorB.R + errorRange && colorA.R >= colorB.R - errorRange && colorA.G <= colorB.G + errorRange && colorA.G >= colorB.G - errorRange && colorA.B <= colorB.B + errorRange && colorA.B >= colorB.B - errorRange; } public bool ListContainsPoint(List<System.Drawing.Point> listPoint, System.Drawing.Point point, double errorRange = 10) { bool isExist = false; foreach (var item in listPoint) { if (item.X <= point.X + errorRange && item.X >= point.X - errorRange && item.Y <= point.Y + errorRange && item.Y >= point.Y - errorRange) { isExist = true; } } return isExist; } }
最后项目实施发现速度不快，只能弃用，网上查询 发现有AForge实现方式。引用
private void button3_Click(object sender, EventArgs e) { System.Drawing.Bitmap sourceImage = ConvertToFormat(System.Drawing.Image.FromFile(@"C:\Users\zaranet\Desktop\da.png"), PixelFormat.Format24bppRgb); System.Drawing.Bitmap template = ConvertToFormat(System.Drawing.Image.FromFile(@"C:\Users\zaranet\Desktop\xiao.png"), PixelFormat.Format24bppRgb); // create template matching algorithm's instance // (set similarity threshold to 92.5%) ExhaustiveTemplateMatching tm = new ExhaustiveTemplateMatching(0.921f); // find all matchings with specified above similarity TemplateMatch[] matchings = tm.ProcessImage(sourceImage, template); // highlight found matchings BitmapData data = sourceImage.LockBits( new Rectangle(0, 0, sourceImage.Width, sourceImage.Height), ImageLockMode.ReadWrite, sourceImage.PixelFormat); foreach (TemplateMatch m in matchings) { Drawing.Rectangle(data, m.Rectangle, Color.White); MessageBox.Show(m.Rectangle.Location.ToString()); // do something else with matching } sourceImage.UnlockBits(data); } public Bitmap ConvertToFormat(System.Drawing.Image image, PixelFormat format) { Bitmap copy = new Bitmap(image.Width, image.Height, format); using (Graphics gr = Graphics.FromImage(copy)) { gr.DrawImage(image, new Rectangle(0, 0, copy.Width, copy.Height)); } return copy; }
速度略快吧。
