Canny边缘检测算法C#源码

[算法说明]

Canny边缘检测算法可以分为4步：高斯滤波器平滑处理、梯度计算、非极大值抑制、双阈值边缘检

测和边缘连接。

1，高斯滤波器平滑处理。由于图像中经常包含一些高斯噪声，因此在边缘检测前我们要先用高斯

滤波器对其进行滤波，为了方便，通常是使用一些高斯模板，这里我们使用如下的高斯滤波器模板。

Canny边缘检测算法C#源码

/// <summary>
/// Canny edge detect process.
/// </summary>
/// <param name="src">The source image.</param>
/// <param name="highThreshould">The high threshould value. </param>
/// <param name="lowThreshould">The low threshould value. </param>
/// <returns></returns>
public static WriteableBitmap CannyedgedetectProcess(WriteableBitmap src,int highThreshould,int lowThreshould)////图像油画效果
{
if (src != null)
{
int w = src.PixelWidth;
int h = src.PixelHeight;
WriteableBitmap srcImage = new WriteableBitmap(w, h);
byte[] temp = src.PixelBuffer.ToArray();
byte[] tempMask = (byte[])temp.Clone();
int[,] srcBytes = new int[w, h];
for (int j = 0; j < h; j++)
{
for (int i = 0; i < w; i++)
{
srcBytes[i, j] = (int)(tempMask[i * 4 + j * w * 4] * 0.114 + tempMask[i * 4 + 1 + j * w * 4] * 0.587 + tempMask[i * 4 + 2 + j * w * 4] * 0.299);
}
}
float gradientMax = 0;
float[,] gradient = new float[w, h];
byte[,] degree = new byte[w, h];
GaussFilter(ref srcBytes, w, h);
GetGradientDegree(srcBytes, ref gradient, ref degree, ref gradientMax, w, h);
NonMaxMini(gradient, ref srcBytes, gradientMax, w, h, degree);
TwoThreshouldJudge(highThreshould, lowThreshould, ref srcBytes, w, h);
for (int j = 0; j < h; j++)
{
for (int i = 0; i < w; i++)
{
temp[i * 4 + j * w * 4] = temp[i * 4 + 1 + j * w * 4] = temp[i * 4 + 2 + j * w * 4] = (byte)srcBytes[i, j];
}
}
Stream sTemp = srcImage.PixelBuffer.AsStream();
sTemp.Seek(0, SeekOrigin.Begin);
sTemp.Write(temp, 0, w * 4 * h);
return srcImage;
}
else
{
return null;
}
}
//高斯滤波
private static void GaussFilter(ref int[,] src, int x, int y)
{
for (int j = 1; j < y - 1; j++)
{
for (int i = 1; i < x - 1; i++)
{
src[i, j] = (4 * src[i, j] + src[i - 1, j - 1] + src[i + 1, j - 1] + src[i - 1, j + 1] + src[i + 1, j + 1] + 2 * src[i, j - 1] + 2 * src[i - 1, j] + 2 * src[i, j + 1] + 2 * src[i + 1, j]) / 16;
}
}
}
//梯度相位角获取
private static void GetGradientDegree(int[,] srcBytes, ref float[,] gradient, ref byte[,] degree, ref float GradientMax, int x, int y)
{
gradient = new float[x, y];
degree = new byte[x, y];
int gx, gy;
int temp;
double div;
for (int j = 1; j < y - 1; j++)
{
for (int i = 1; i < x - 1; i++)
{
gx = srcBytes[i + 1, j - 1] + 2 * srcBytes[i + 1, j] + srcBytes[i + 1, j + 1] - srcBytes[i - 1, j - 1] - 2 * srcBytes[i - 1, j] - srcBytes[i - 1, j + 1];
gy = srcBytes[i - 1, j - 1] + 2 * srcBytes[i, j - 1] + srcBytes[i + 1, j - 1] - srcBytes[i - 1, j + 1] - 2 * srcBytes[i, j + 1] - srcBytes[i + 1, j + 1];
gradient[i, j] = (float)Math.Sqrt((double)(gx * gx + gy * gy));
if (GradientMax < gradient[i, j])
{
GradientMax = gradient[i, j];
}
if (gx == 0)
{
temp = (gy == 0) ? 0 : 90;
}
else
{
div = (double)gy / (double)gx;
if (div < 0)
{
temp = (int)(180 - Math.Atan(-div) * 180 / Math.PI);
}
else
{
temp = (int)(Math.Atan(div) * 180 / Math.PI);
}
if (temp < 22.5)
{
temp = 0;
}
else if (temp < 67.5)
{
temp = 45;
}
else if (temp < 112.5)
{
temp = 90;
}
else if (temp < 157.5)
{
temp = 135;
}
else
temp = 0;
}
degree[i, j] = (byte)temp;
}
}
}
//非极大值抑制
private static void NonMaxMini(float[,] gradient, ref int[,] srcBytes, float GradientMax, int x, int y, byte[,] degree)
{
float leftPixel = 0, rightPixel = 0;
for (int j = 1; j < y - 1; j++)
{
for (int i = 1; i < x - 1; i++)
{
switch (degree[i, j])
{
case 0:
leftPixel = gradient[i - 1, j];
rightPixel = gradient[i + 1, j];
break;
case 45:
leftPixel = gradient[i - 1, j + 1];
rightPixel = gradient[i + 1, j - 1];
break;
case 90:
leftPixel = gradient[i, j + 1];
rightPixel = gradient[i, j - 1];
break;
case 135:
leftPixel = gradient[i + 1, j + 1];
rightPixel = gradient[i - 1, j - 1];
break;
default:
break;
}
if ((gradient[i, j] < leftPixel) || (gradient[i, j] < rightPixel))
{
srcBytes[i, j] = 0;
}
else
{
srcBytes[i, j] = (int)(255 * gradient[i, j] / GradientMax);
}
}
}
}
//双阈值边缘判断
private static void TwoThreshouldJudge(int highThreshold, int lowThreshould, ref int[,] srcBytes, int x, int y)
{
for (int j = 1; j < y - 1; j++)
{
for (int i = 1; i < x - 1; i++)
{
if (srcBytes[i, j] > highThreshold)
{
srcBytes[i, j] = 255;
}
else if (srcBytes[i, j] < lowThreshould)
{
srcBytes[i, j] = 0;
}
else
{
if (srcBytes[i - 1, j - 1] < highThreshold && srcBytes[i, j - 1] < highThreshold && srcBytes[i + 1, j - 1] < highThreshold && srcBytes[i - 1, j] < highThreshold
&& srcBytes[i + 1, j] < highThreshold && srcBytes[i - 1, j + 1] < highThreshold && srcBytes[i, j + 1] < highThreshold && srcBytes[i + 1, j + 1] < highThreshold)
{
srcBytes[i, j] = 0;
}
else
srcBytes[i, j] = 255;
}
}
}
}

Canny边缘检测算法C#源码