我试着为AForge.Imaging.Filters
添加一个新的自适应阈值方法我在
下添加了新的cs文件来源\影像\滤镜\自适应二值化
以下是阈值方法的代码
namespace AForge.Imaging.Filters
{
using System;
using System.Collections.Generic;
using System.Drawing;
using System.Drawing.Imaging;
using AForge.Imaging;
class SauvolaAdaptiveThresholding : BaseInPlacePartialFilter
{
private const float DEFAULT_WeightingFactor = 0.3f;
private const short DEFAULT_WindowSize = 40;
private float weightingFactor ;
private short windowSize ;
// private format translation dictionary
private Dictionary<PixelFormat, PixelFormat> formatTranslations = new Dictionary<PixelFormat, PixelFormat>();
/// <summary>
/// Format translations dictionary.
/// </summary>
public override Dictionary<PixelFormat,PixelFormat> FormatTranslations
{
get { return formatTranslations; }
}
public float WeightingFactor
{
get{return this.weightingFactor;}
set{this.weightingFactor = value;}
}
public short WindowSize
{
get{return this.windowSize;}
set{this.windowSize = value;}
}
public SauvolaAdaptiveThresholding() :
this(DEFAULT_WeightingFactor,DEFAULT_WindowSize) { }
public SauvolaAdaptiveThresholding(float _weightFact , short _wsize)
{
this.WeightingFactor = _weightFact;
this.WindowSize =_wsize;
// initialize format translation dictionary
formatTranslations[PixelFormat.Format8bppIndexed] = PixelFormat.Format8bppIndexed;
formatTranslations[PixelFormat.Format16bppGrayScale] = PixelFormat.Format16bppGrayScale;
}
protected override unsafe void ProcessFilter(UnmanagedImage image, Rectangle rect)
{
int whalf = windowSize >> 1; //half of windowsize
whalf = windowSize >> 1;
byte* ptr = (byte*)image.ImageData.ToPointer(); //input
// Calculate the integral image, and integral of the squared image
ulong[,] integral_image = new ulong[image.Width , image.Height];
ulong[,] rowsum_image = new ulong[image.Width , image.Height];
ulong[,] integral_sqimg = new ulong[image.Width , image.Height];
ulong[,] rowsum_sqimg = new ulong[image.Width , image.Height];
int xmin, ymin, xmax, ymax, index;
double diagsum, idiagsum, diff, sqdiagsum, sqidiagsum, sqdiff, area;
double mean, std, threshold;
for (int j = 0; j < image.Height; j++)
{
rowsum_image[0, j] = (ulong)*(ptr + j);
rowsum_sqimg[0, j] = rowsum_image[0, j] * rowsum_image[0, j];
}
for (int i = 1; i < image.Width; i++)
{
for (int j = 0; j < image.Height; j++)
{
index = j * image.Width + i;
rowsum_image[i, j] = rowsum_image[i - 1, j] + (ulong)*(ptr + index);
rowsum_sqimg[i, j] = rowsum_sqimg[i - 1, j] + (ulong)(*(ptr + index) * *(ptr + index));
}
}
for (int i = 0; i < image.Width; i++)
{
integral_image[i, 0] = rowsum_image[i, 0];
integral_sqimg[i, 0] = rowsum_sqimg[i, 0];
}
for (int i = 0; i < image.Width; i++)
{
for (int j = 1; j < image.Height; j++)
{
integral_image[i, j] = integral_image[i, j - 1] + rowsum_image[i, j];
integral_sqimg[i, j] = integral_sqimg[i, j - 1] + rowsum_sqimg[i, j];
}
}
//Calculate the mean and standard deviation using the integral image
for (int i = 0; i < image.Width; i++)
{
for (int j = 0; j < image.Height; j++)
{
xmin = Math.Max(0, i - whalf);//max(0, i - whalf);
ymin = Math.Max(0, j - whalf);
xmax = Math.Min(image.Width - 1, i + whalf);
ymax = Math.Min(image.Height - 1, j + whalf);
area = (xmax - xmin + 1) * (ymax - ymin + 1);
if (xmin == 0 && ymin == 0)
{ // Point at origin
diff = integral_image[xmax, ymax];
sqdiff = integral_sqimg[xmax, ymax];
}
else if (xmin == 0 && ymin != 0)
{ // first column
diff = integral_image[xmax, ymax] - integral_image[xmax, ymin - 1];
sqdiff = integral_sqimg[xmax, ymax] - integral_sqimg[xmax, ymin - 1];
}
else if (xmin != 0 && ymin == 0)
{ // first row
diff = integral_image[xmax, ymax] - integral_image[xmin - 1, ymax];
sqdiff = integral_sqimg[xmax, ymax] - integral_sqimg[xmin - 1, ymax];
}
else
{ // rest of the image
diagsum = integral_image[xmax, ymax] + integral_image[xmin - 1, ymin - 1];
idiagsum = integral_image[xmax, ymin - 1] + integral_image[xmin - 1, ymax];
diff = diagsum - idiagsum;
sqdiagsum = integral_sqimg[xmax, ymax] + integral_sqimg[xmin - 1, ymin - 1];
sqidiagsum = integral_sqimg[xmax, ymin - 1] + integral_sqimg[xmin - 1, ymax];
sqdiff = sqdiagsum - sqidiagsum;
}
mean = diff / area;
std = Math.Sqrt((sqdiff - diff * diff / area) / (area - 1));
threshold = mean * (1 + WeightingFactor * ((std / 128) - 1));
if ((double)*(ptr + (j * image.Width + i)) < threshold)//if (gray_image[i, j] < threshold)
*(ptr + (j * image.Width + i)) = 0;
else
*(ptr + (j * image.Width + i)) = 255;
}
}
}
}
}
但是当我构建项目并使用AForge.Imaging.dll时，上面的类不可用。当我尝试使用对象浏览器时，我会看到除了我新添加的类之外的所有其他类。
有人可以告诉我我做错了什么吗？
答案 0 :(得分：2)
需要公开
public class SauvolaAdaptiveThresholding : BaseInPlacePartialFilter
您可以在此处找到有关C＃访问修饰符的更多信息：http://msdn.microsoft.com/en-us/library/ms173121.aspx