/// <summary>
/// 反向投影(3維),需搭配3維的直方圖計算
/// </summary>
/// <param name="template">樣板值方圖</param>
/// <param name="observedSrcImg">要比對觀察的影像</param>
/// <param name="isNormalized">是否要標準化</param>
/// <param name="factor">標準化參數,預設1200000d</param>
/// <returns>回除灰階的觀察影像(越白代表匹配的顏色越高)</returns>
public static Image <Gray, Byte> HSVBackProject(DenseHistogram template, Image <Bgr, Byte> observedSrcImg, bool isNormalized = true, double factor = 1200000d)
{
try
{
DenseHistogram templateHist = new DenseHistogram(new int[] { template.BinDimension[0].Size, template.BinDimension[1].Size, template.BinDimension[2].Size }, new RangeF[] { new RangeF(0, h_max_range), new RangeF(0, s_max_range), new RangeF(0, v_max_range) });
template.Copy(templateHist);
Image <Bgr, Byte> observedImg = observedSrcImg.Copy();
IntPtr hsv = CvInvoke.cvCreateImage(CvInvoke.cvGetSize(observedImg), Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 3);
IntPtr h_plane = CvInvoke.cvCreateImage(CvInvoke.cvGetSize(observedImg), Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 1);
IntPtr s_plane = CvInvoke.cvCreateImage(CvInvoke.cvGetSize(observedImg), Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 1);
IntPtr v_plane = CvInvoke.cvCreateImage(CvInvoke.cvGetSize(observedImg), Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 1);
IntPtr[] observed_planes = new IntPtr[3] {
h_plane, s_plane, v_plane
};
//Image<Gray, Byte> h_planeImg = IplImagePointerToEmgucvImage<Gray, Byte>(h_plane);
//Image<Gray, Byte> s_planeImg = IplImagePointerToEmgucvImage<Gray, Byte>(s_plane);
CvInvoke.cvCvtColor(observedImg, hsv, Emgu.CV.CvEnum.COLOR_CONVERSION.CV_BGR2HSV);
CvInvoke.cvSplit(hsv, h_plane, s_plane, v_plane, System.IntPtr.Zero); // 分离的单通道数组d
if (isNormalized)
{
templateHist.Normalize(factor);
}
IntPtr backProj = CvInvoke.cvCreateImage(CvInvoke.cvGetSize(observedImg), Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 1);
CvInvoke.cvZero(backProj);
CvInvoke.cvCalcBackProject(observed_planes, backProj, templateHist);
return(EmguFormatConvetor.IplImagePointerToEmgucvImage <Gray, Byte>(backProj));
}
catch (Exception ex)
{
throw new InvalidOperationException(ex.Message);
}
}
/// <summary>
/// 等化影像
/// </summary>
/// <param name="srcImg">要等化的影像</param>
/// <returns>回傳等化過的影像</returns>
public static Image <Bgr, Byte> EqualizationImage(Image <Bgr, Byte> srcImg)
{
IntPtr dstImg = CvInvoke.cvCreateImage(CvInvoke.cvGetSize(srcImg), IPL_DEPTH.IPL_DEPTH_8U, 3);
IntPtr redImage = CvInvoke.cvCreateImage(CvInvoke.cvGetSize(srcImg), IPL_DEPTH.IPL_DEPTH_8U, 1);
IntPtr greenImage = CvInvoke.cvCreateImage(CvInvoke.cvGetSize(srcImg), IPL_DEPTH.IPL_DEPTH_8U, 1);
IntPtr blueImage = CvInvoke.cvCreateImage(CvInvoke.cvGetSize(srcImg), IPL_DEPTH.IPL_DEPTH_8U, 1);
CvInvoke.cvSplit(srcImg, blueImage, greenImage, redImage, IntPtr.Zero);
CvInvoke.cvEqualizeHist(blueImage, blueImage);
CvInvoke.cvEqualizeHist(greenImage, greenImage);
CvInvoke.cvEqualizeHist(redImage, redImage);
CvInvoke.cvMerge(blueImage, greenImage, redImage, IntPtr.Zero, dstImg);
return(EmguFormatConvetor.IplImagePointerToEmgucvImage <Bgr, Byte>(dstImg));
}
/// <summary>
/// 2D值方圖(色調與飽和度) 的繪製,使用emgucv提供的cvInvoke去調用opencv的函式
/// 繪製與範例的值方圖一致目前先採用
/// </summary>
/// <param name="histDense"></param>
/// <returns>回傳繪製值方圖的影像,直接顯示即可</returns>
public static Image <Bgr, Byte> Generate2DHistogramImgForDraw(DenseHistogram histDense)
{
try
{
float max_value = 0.0f;
int[] a1 = new int[100];
int[] b1 = new int[100];
float ax = 0;
int h_bins = histDense.BinDimension[0].Size;
int s_bins = histDense.BinDimension[1].Size;
//1.使用Intptr
// CvInvoke.cvGetMinMaxHistValue(histPtr, ref ax, ref max_value, a1, b1);
//2.emgucv的DenseHistogram資料格式也可使用cvInvoke的openCV函式
CvInvoke.cvGetMinMaxHistValue(histDense, ref ax, ref max_value, a1, b1);
/* 设置直方图显示图像 */
int height = 300;
int width;
//如果設定的bins超過視窗設定的顯示範圍,另外給予可以符合用額外的彈出視窗顯示的值
if (h_bins * s_bins > 800)
{
width = h_bins * s_bins * 2;
}
else
{
width = 800;
}
IntPtr hist_img = CvInvoke.cvCreateImage(new System.Drawing.Size(width, height), Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 3);
CvInvoke.cvZero(hist_img);
/* 用来进行HSV到RGB颜色转换的临时单位图像 */
IntPtr hsv_color = CvInvoke.cvCreateImage(new System.Drawing.Size(1, 1), Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 3);
IntPtr rgb_color = CvInvoke.cvCreateImage(new System.Drawing.Size(1, 1), Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 3);
int bin_w = width / (h_bins * s_bins);
for (int h = 0; h < h_bins; h++)
{
for (int s = 0; s < s_bins; s++)
{
int i = h * s_bins + s;
/* 获得直方图中的统计次数，计算显示在图像中的高度 */
//
//取得值方圖的數值位置,以便之後存成檔案
//1.Intptr
//double bin_val = CvInvoke.cvQueryHistValue_2D(histPtr, h, s);
//2.DenseHistogram
double bin_val = CvInvoke.cvQueryHistValue_2D(histDense, h, s);
int intensity = (int)System.Math.Round(bin_val * height / max_value);
/* 获得当前直方图代表的颜色，转换成RGB用于绘制 */
CvInvoke.cvSet2D(hsv_color, 0, 0, new Emgu.CV.Structure.MCvScalar(h * 180.0f / h_bins, s * 255.0f / s_bins, 255, 0));
CvInvoke.cvCvtColor(hsv_color, rgb_color, COLOR_CONVERSION.CV_HSV2BGR);
Emgu.CV.Structure.MCvScalar color = CvInvoke.cvGet2D(rgb_color, 0, 0);
CvInvoke.cvRectangle(hist_img, new System.Drawing.Point(i * bin_w, height), new System.Drawing.Point((i + 1) * bin_w, height - intensity), color, -1, Emgu.CV.CvEnum.LINE_TYPE.EIGHT_CONNECTED, 0);
}
}
/*
*使用openCV函式繪製
* CvInvoke.cvNamedWindow("Source");
* CvInvoke.cvShowImage("Source", this.srcImage);
* CvInvoke.cvNamedWindow("H-S Histogram");
* CvInvoke.cvShowImage("H-S Histogram", hist_img);
* CvInvoke.cvWaitKey(0);
* */
return(EmguFormatConvetor.IplImagePointerToEmgucvImage <Bgr, Byte>(hist_img));
}
catch (Exception ex)
{
throw new InvalidOperationException(ex.Message);
}
}
//////////////////////////////////////////////////////////////////////////////////////////////
/// <summary>
/// drawing hue color still have problem
/// 1D值方圖(色調) 的繪製,使用emgucv提供的cvInvoke去調用opencv的函式
/// 繪製與範例的值方圖一致目前先採用
/// </summary>
/// <param name="histDense"></param>
/// <returns>回傳繪製值方圖的影像,直接顯示即可</returns>
public static Image <Bgr, Byte> Generate1DHistogramImgForDraw(DenseHistogram histDense)
{
try
{
float max_value = 0.0f;
int[] a1 = new int[100];
int[] b1 = new int[100];
float ax = 0;
int h_bins = histDense.BinDimension[0].Size;
//1.使用Intptr
// CvInvoke.cvGetMinMaxHistValue(histPtr, ref ax, ref max_value, a1, b1);
//2.emgucv的DenseHistogram資料格式也可使用cvInvoke的openCV函式
CvInvoke.cvGetMinMaxHistValue(histDense, ref ax, ref max_value, a1, b1);
/* 取最大的顏色的位置 並換成RGB
* foreach (int index in a1)
* {
* Console.WriteLine("location="+index+",H Color = "+ HueToBgr(index * 180.0d / h_bins));
* }
* */
/* 设置直方图显示图像 */
int height = 240;
int width = 800;
IntPtr hist_img = CvInvoke.cvCreateImage(new System.Drawing.Size(width, height), Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 3);
CvInvoke.cvZero(hist_img);
/* 用来进行HSV到RGB颜色转换的临时单位图像 */
IntPtr hsv_color = CvInvoke.cvCreateImage(new System.Drawing.Size(1, 1), Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 3);
IntPtr rgb_color = CvInvoke.cvCreateImage(new System.Drawing.Size(1, 1), Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 3);
int bin_w = width / (h_bins);
for (int h = 0; h < h_bins; h++)
{
/* 获得直方图中的统计次数，计算显示在图像中的高度 */
//
//取得值方圖的數值位置,以便之後存成檔案
//2.DenseHistogram
double bin_val = CvInvoke.cvQueryHistValue_1D(histDense, h);
int intensity = (int)System.Math.Round(bin_val * height / max_value);
/* 获得当前直方图代表的hue颜色，转换成RGB用于绘制 */
CvInvoke.cvRectangle(hist_img, new System.Drawing.Point(h * bin_w, height),
new System.Drawing.Point((h + 1) * bin_w, height - intensity),
HueToBgr(h * 180.0d / h_bins), -1, Emgu.CV.CvEnum.LINE_TYPE.EIGHT_CONNECTED, 0);
}
/*
*使用openCV函式繪製
* CvInvoke.cvNamedWindow("Source");
* CvInvoke.cvShowImage("Source", this.srcImage);
* CvInvoke.cvNamedWindow("H-S Histogram");
* CvInvoke.cvShowImage("H-S Histogram", hist_img);
* CvInvoke.cvWaitKey(0);
* */
return(EmguFormatConvetor.IplImagePointerToEmgucvImage <Bgr, Byte>(hist_img));
}
catch (Exception ex)
{
throw new InvalidOperationException(ex.Message);
}
}
