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。
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