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c# - 校正扫描图像

转载 作者:太空狗 更新时间:2023-10-30 00:12:47 36 4
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我在 OMR 项目中工作,我们使用的是 C#。当我们来扫描答卷时,图像是歪斜的。我们怎样才能消除它们?

最佳答案

可用的 VB.Net 代码 here ,但是由于您要求使用 C#,因此这里是他们的 Deskew 类的 C# 翻译(注意:二值化(严格来说不是必需的,但效果更好)和旋转是留给用户的练习)。

 public class Deskew
{
// Representation of a line in the image.
private 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;
}


// The Bitmap
Bitmap _internalBmp;

// The range of angles to search for lines
const double ALPHA_START = -20;
const double ALPHA_STEP = 0.2;
const int STEPS = 40 * 5;
const double STEP = 1;

// Precalculation of sin and cos.
double[] _sinA;
double[] _cosA;

// Range of d
double _min;


int _count;
// Count of points that fit in a line.
int[] _hMatrix;

public Bitmap DeskewImage(Bitmap image, int type, int binarizeThreshold)
{
Size oldSize = image.Size;

_internalBmp = BitmapFunctions.Resize(image, new Size(1000, 1000), true, image.PixelFormat);
Binarize(_internalBmp, binarizeThreshold);


return Rotate(image, GetSkewAngle());
}

// Calculate the skew angle of the image cBmp.
private double GetSkewAngle()
{
// Hough Transformation
Calc();

// Top 20 of the detected lines in the image.
HougLine[] hl = GetTop(20);

// Average angle of the lines
double sum = 0;
int count = 0;
for (int i = 0; i <= 19; i++)
{
sum += hl[i].Alpha;
count += 1;
}
return sum / count;
}

// Calculate the Count lines in the image with most points.
private HougLine[] GetTop(int count)
{
HougLine[] hl = new HougLine[count];

for (int i = 0; i <= count - 1; i++)
{
hl[i] = new HougLine();
}
for (int i = 0; i <= _hMatrix.Length - 1; i++)
{
if (_hMatrix[i] > hl[count - 1].Count)
{
hl[count - 1].Count = _hMatrix[i];
hl[count - 1].Index = i;
int j = count - 1;
while (j > 0 && hl[j].Count > hl[j - 1].Count)
{
HougLine tmp = hl[j];
hl[j] = hl[j - 1];
hl[j - 1] = tmp;
j -= 1;
}
}
}

for (int i = 0; i <= count - 1; i++)
{
int dIndex = hl[i].Index / STEPS;
int alphaIndex = hl[i].Index - dIndex * STEPS;
hl[i].Alpha = GetAlpha(alphaIndex);
//hl[i].D = dIndex + _min;
}

return hl;
}


// Hough Transforamtion:
private void Calc()
{
int hMin = _internalBmp.Height / 4;
int hMax = _internalBmp.Height * 3 / 4;

Init();
for (int y = hMin; y <= hMax; y++)
{
for (int x = 1; x <= _internalBmp.Width - 2; x++)
{
// Only lower edges are considered.
if (IsBlack(x, y))
{
if (!IsBlack(x, y + 1))
{
Calc(x, y);
}
}
}
}
}

// Calculate all lines through the point (x,y).
private void Calc(int x, int y)
{
int alpha;

for (alpha = 0; alpha <= STEPS - 1; alpha++)
{
double d = y * _cosA[alpha] - x * _sinA[alpha];
int calculatedIndex = (int)CalcDIndex(d);
int index = calculatedIndex * STEPS + alpha;
try
{
_hMatrix[index] += 1;
}
catch (Exception ex)
{
System.Diagnostics.Debug.WriteLine(ex.ToString());
}
}
}
private double CalcDIndex(double d)
{
return Convert.ToInt32(d - _min);
}
private bool IsBlack(int x, int y)
{
Color c = _internalBmp.GetPixel(x, y);
double luminance = (c.R * 0.299) + (c.G * 0.587) + (c.B * 0.114);
return luminance < 140;
}

private void Init()
{
// Precalculation of sin and cos.
_cosA = new double[STEPS];
_sinA = new double[STEPS];

for (int i = 0; i < STEPS; i++)
{
double angle = GetAlpha(i) * Math.PI / 180.0;
_sinA[i] = Math.Sin(angle);
_cosA[i] = Math.Cos(angle);
}

// Range of d:
_min = -_internalBmp.Width;
_count = (int)(2 * (_internalBmp.Width + _internalBmp.Height) / STEP);
_hMatrix = new int[_count * STEPS];


}

private static double GetAlpha(int index)
{
return ALPHA_START + index * ALPHA_STEP;
}
}

关于c# - 校正扫描图像,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/2394405/

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