/// <summary>
/// 取得一个样本的特征
/// </summary>
/// <param name="bmpSource">源图像，需24位或32位真彩位图</param>
/// <param name="template">基础分类器模板</param>
/// <param name="sampletype">样本类型，1表示正样本，－1表示负样本</param>
/// <returns>返回一个样本的特征</returns>
public static SampleFeature GetSampleFeature(Bitmap bmpSource, BaseClassifierTemplate template, int sampletype)
{
SampleFeature sf = null;
Bitmap bmp = bmpSource;
if (bmp != null && (bmp.PixelFormat == PixelFormat.Format24bppRgb || bmp.PixelFormat ==
PixelFormat.Format32bppRgb || bmp.PixelFormat == PixelFormat.Format32bppArgb))
{
// 将图像调整至模板大小
if (bmp.Width != template.BmpWidth || bmp.Height != template.BmpHeight)
{
bmp = ImgOper.ResizeImage(bmpSource, template.BmpWidth, template.BmpHeight);
}
bmp = ImgOper.Grayscale(bmpSource);
int[,] igram = ImgOper.Integrogram(bmp, 1);
sf = new SampleFeature();
sf.GroupNum = template.GroupNum;
sf.FeatureNum = template.FeatureNum;
sf.SampleType = sampletype;
sf.FeatureValue = BaseClassifierTemplate.GetFeatureCodeGroup(igram, bmp.Width, bmp.Height, template, 0, 0);
}
return(sf);
}
/// <summary>
/// 用模板去检测图像中的物体
/// </summary>
/// <param name="bmpSource">源图像，需24位或32位真彩位图</param>
/// <param name="template">基础分类器模板</param>
/// <param name="fern">Fern</param>
/// <returns></returns>
public static RectangleCollection DetectObject(Bitmap bmpSource, BaseClassifierTemplate template, Fern fern)
{
RectangleCollection rc = new RectangleCollection();
Bitmap bmp = bmpSource;
if (bmpSource.Width < template.BmpWidth || bmpSource.Height < template.BmpHeight)
{
return(null);
}
if (bmp != null && (bmp.PixelFormat == PixelFormat.Format24bppRgb || bmp.PixelFormat ==
PixelFormat.Format32bppRgb || bmp.PixelFormat == PixelFormat.Format32bppArgb))
{
UInt32[] featurecode = null;
bmp = ImgOper.Grayscale(bmpSource);
int[,] igram = ImgOper.Integrogram(bmp, 1);
while (template.BmpWidth < bmp.Width && template.BmpHeight < bmp.Height)
{
for (int y = 0; y < bmp.Height - template.BmpHeight + 1; y += (template.BmpHeight / 10))
{
for (int x = 0; x < bmp.Width - template.BmpWidth + 1; x += (template.BmpWidth / 10))
{
//int posnum = 0;
//int negnum = 0;
featurecode = BaseClassifierTemplate.GetFeatureCodeGroup(igram, bmp.Width, bmp.Height, template, x, y);
double prob = 0;
for (int i = 0; i < template.GroupNum; i++)
{
prob += fern.Probability[featurecode[i]];
//prob = fern.Probability[featurecode[i]];
//if (prob > 0.5)
//{
// posnum++;
//}
//else
//{
// negnum++;
//}
}
prob = prob / template.GroupNum;
if (prob > 0.5)
//if (posnum > negnum)
{
Rectangle rect = new Rectangle(x, y, template.BmpWidth, template.BmpHeight);
rc.Add(rect);
}
}
}
template.ResizeTemplate(1.2);
}
}
return(rc);
}
/// <summary>
/// 用训练好的模型测试已标记样本的类别
/// </summary>
/// <param name="sample">已标记样本图像</param>
/// <param name="template">基础分类器模板</param>
/// <param name="fern">Fern</param>
/// <returns>返回测试结果，类别</returns>
public static int DetectSample(Bitmap sample, BaseClassifierTemplate template, Fern fern)
{
Bitmap bmp = null;
if (sample.Width != template.BmpWidth || sample.Height != template.BmpHeight)
{
bmp = ImgOper.ResizeImage(sample, template.BmpWidth, template.BmpHeight);
}
else
{
bmp = sample;
}
if (bmp != null && (bmp.PixelFormat == PixelFormat.Format24bppRgb || bmp.PixelFormat ==
PixelFormat.Format32bppRgb || bmp.PixelFormat == PixelFormat.Format32bppArgb))
{
bmp = ImgOper.Grayscale(bmp);
int[,] igram = ImgOper.Integrogram(bmp, 1);
UInt32[] featurecode = BaseClassifierTemplate.GetFeatureCodeGroup(igram, bmp.Width, bmp.Height, template, 0, 0);
double prob = 0;
for (int i = 0; i < template.GroupNum; i++)
{
prob += fern.Probability[featurecode[i]];
}
prob = prob / template.GroupNum;
if (prob > 0.5)
{
return(1);
}
else
{
return(-1);
}
}
return(0);
}
/// <summary>
/// 获取一个检测窗口对应的图像中所有特征组
/// </summary>
/// <param name="igram">积分图</param>
/// <param name="gramwidth">图像宽度</param>
/// <param name="gramheight">图像高度</param>
/// <param name="template">模板</param>
/// <param name="wx">检测窗口左上角X坐标</param>
/// <param name="wy">检测窗口左上角Y坐标</param>
/// <returns></returns>
public static UInt32[] GetFeatureCodeGroup(int[,] igram, int gramwidth, int gramheight, BaseClassifierTemplate template, int wx, int wy)
{
UInt32[] featurevalue = new UInt32[template.GroupNum];
if (wx + template.BmpWidth > gramwidth || wy + template.BmpHeight > gramheight)
{
return(featurevalue);
}
for (int i = 0; i < template.GroupNum; i++)
{
UInt32 fvalue = 0;
for (int j = 0; j < template.FeatureNum; j++)
{
fvalue = fvalue << 1; // 左移1位
Rectangle r = template.BitFeatures[i, j];
int x = r.X + wx; // 最左侧的x
int y = r.Y + wy; // 最上面的y
int w = r.Width;
int h = r.Height;
int xm = x + (w - 1) / 2; // 中间的x
int ym = y + (h - 1) / 2; // 中间的y
int xb = x + (w - 1); // 最右侧的x
int yb = y + (h - 1); // 最下面的y
if (r.Width > r.Height) // 横向特征
{
int feature_left = igram[yb, xm] + igram[y, x] - igram[y, xm] - igram[yb, x];
int feature_right = igram[yb, xb] + igram[y, xm] - igram[y, xb] - igram[yb, xm];
if (feature_left > feature_right)
{
fvalue++;
}
}
else if (r.Width == 1) // 纵向特征
{
int feature_up = igram[ym, xb] + igram[y, x] - igram[y, xb] - igram[ym, x];
int feature_bottom = igram[yb, xb] + igram[ym, x] - igram[ym, xb] - igram[yb, x];
if (feature_up > feature_bottom)
{
fvalue++;
}
}
}
featurevalue[i] = fvalue; // 一个组中的特征数不能超过16个
}
return(featurevalue);
}
