using System; using System.Collections.Generic; using System.ComponentModel; using System.Data; using System.Drawing; using System.Text; using System.Windows.Forms; using System.Collections; using System.Diagnostics; using System.Drawing.Imaging;//窗體調用private Bitmap RotateImage(Bitmap bmp, double angle){Graphics g = null;Bitmap tmp = new Bitmap(bmp.Width, bmp.Height, PixelFormat.Format32bppRgb);tmp.SetResolution(bmp.HorizontalResolution, bmp.VerticalResolution);g = Graphics.FromImage(tmp);try{g.FillRectangle(Brushes.White, 0, 0, bmp.Width, bmp.Height);g.RotateTransform((float)angle);g.DrawImage(bmp, 0, 0);}finally{g.Dispose();}return tmp;}private void button1_Click(object sender, EventArgs e){string fnIn = "f:\\test\\image0097_4.tif";string fnOut = "f:\\test\\output.tif";Bitmap bmpIn = new Bitmap(fnIn);gmseDeskew sk = new gmseDeskew(bmpIn);double skewangle = sk.GetSkewAngle();Bitmap bmpOut = RotateImage(bmpIn, -skewangle);bmpOut.Save(fnOut, ImageFormat.Tiff);//此處簡單保存，可采用壓縮方式保存 }#region 算法處理類public class gmseDeskew{public class HougLine{// Count of points in the line.public int Count;// Index in Matrix.public int Index;// The line is represented as all x,y that solve y*cos(alpha)-x*sin(alpha)=d public double Alpha;public double d;}Bitmap cBmp;double cAlphaStart = -20;double cAlphaStep = 0.2;int cSteps = 40 * 5;double[] cSinA;double[] cCosA;double cDMin;double cDStep = 1;int cDCount;// Count of points that fit in a line.int[] cHMatrix;public double GetSkewAngle(){gmseDeskew.HougLine[] hl = null;int i = 0;double sum = 0;int count = 0;// Hough Transformation Calc();// Top 20 of the detected lines in the image.hl = GetTop(20);// Average angle of the linesfor (i = 0; i <= 19; i++){sum += hl[i].Alpha;count += 1;}return sum / count;}private HougLine[] GetTop(int Count){HougLine[] hl = null;int i = 0;int j = 0;HougLine tmp = null;int AlphaIndex = 0;int dIndex = 0;hl = new HougLine[Count + 1];for (i = 0; i <= Count - 1; i++){hl[i] = new HougLine();}for (i = 0; i <= cHMatrix.Length - 1; i++){if (cHMatrix[i] > hl[Count - 1].Count){hl[Count - 1].Count = cHMatrix[i];hl[Count - 1].Index = i;j = Count - 1;while (j > 0 && hl[j].Count > hl[j - 1].Count){tmp = hl[j];hl[j] = hl[j - 1];hl[j - 1] = tmp; j -= 1;}}}for (i = 0; i <= Count - 1; i++){dIndex = hl[i].Index / cSteps;AlphaIndex = hl[i].Index - dIndex * cSteps;hl[i].Alpha = GetAlpha(AlphaIndex);hl[i].d = dIndex + cDMin;}return hl;}public gmseDeskew(Bitmap bmp){cBmp = bmp;}private void Calc(){int x = 0;int y = 0;int hMin = cBmp.Height / 4;int hMax = cBmp.Height * 3 / 4;Init();for (y = hMin; y <= hMax; y++){for (x = 1; x <= cBmp.Width - 2; x++){ // Only lower edges are considered.if (IsBlack(x, y)){if (!IsBlack(x, y + 1)){Calc(x, y);}}}}}private void Calc(int x, int y){int alpha = 0;double d = 0;int dIndex = 0;int Index = 0;for (alpha = 0; alpha <= cSteps - 1; alpha++){d = y * cCosA[alpha] - x * cSinA[alpha];dIndex = (int)CalcDIndex(d);Index = dIndex * cSteps + alpha;try{cHMatrix[Index] += 1;}catch (Exception ex){Debug.WriteLine(ex.ToString());}}}private double CalcDIndex(double d){return Convert.ToInt32(d - cDMin);}private bool IsBlack(int x, int y){Color c = default(Color);double luminance = 0;c = cBmp.GetPixel(x, y);luminance = (c.R * 0.299) + (c.G * 0.587) + (c.B * 0.114);return luminance < 140;}private void Init(){int i = 0;double angle = 0;// Precalculation of sin and cos. cSinA = new double[cSteps];cCosA = new double[cSteps];for (i = 0; i <= cSteps - 1; i++){angle = GetAlpha(i) * Math.PI / 180.0;cSinA[i] = Math.Sin(angle);cCosA[i] = Math.Cos(angle);} // Range of d: cDMin = -cBmp.Width;cDCount = (int)(2 * (cBmp.Width + cBmp.Height) / cDStep);cHMatrix = new int[cDCount * cSteps + 1];}public double GetAlpha(int Index){return cAlphaStart + Index * cAlphaStep;}}#endregion

具體算法為：由左邊界開始掃描，從開始發現黑色素到黑色素達到平均值，在這個距離內的長度和版心的高度通過直角三角形的函數進行換算，這樣就知道了傾斜的角度。

轉載于:https://www.cnblogs.com/longyi/p/4635014.html

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