private DetectedDoor DoorFromRec(Rectangle rec, Size imageSize)
{
Rectangle boundingBox = rec;
int centerX = (boundingBox.Left + boundingBox.Right) / 2;
int centerY = (boundingBox.Bottom + boundingBox.Top) / 2;
// Get the angle relative to the bottom center of the image
int centerXOffset = centerX - (imageSize.Width / 2);
double angle = -Math.Atan2(-centerY, centerXOffset) - 2 * Math.PI / 4;
double distance = GetEstimatedDistance(rec, imageSize);
DetectedDoor.DetectionConfidence confidence = GetConfidence(boundingBox, imageSize);
return(new DetectedDoor(boundingBox, imageSize, confidence, angle, distance, DetectedDoor.DetectMethod.HAAR));
}
private DetectedDoor DoorFromContour(Contour <Point> contour, ushort[] depthValue, Size imageSize)
{
Rectangle boundingBox = contour.BoundingRectangle;
int left = boundingBox.Left;
int right = boundingBox.Right;
int top = boundingBox.Top;
int bottom = boundingBox.Bottom;
int centerX = (boundingBox.Left + boundingBox.Right) / 2;
int centerY = (boundingBox.Bottom + boundingBox.Top) / 2;
// Get the angle relative to the bottom center of the image
int centerXOffset = centerX - (imageSize.Width / 2);
double angle = -Math.Atan2(-centerY, centerXOffset) - Math.PI / 2;
DetectedDoor.DetectionConfidence confidence = GetConfidence(boundingBox, imageSize);
Rectangle box = contour.BoundingRectangle;
int maxHeight = 424;
int maxWidth = 512;
//calculate average depth at left right and middle
int averDepthLeft, averDepthRight, averDepthMiddle;
int sum = 0;
int pixelCounter = 0;
for (int i = -8; i <= -2; i++)
{
int x = left + i;
for (int y = top; y < bottom; y++)
{
sum += GetDepth(depthValue, maxWidth * y + x);
pixelCounter++;
}
}
averDepthLeft = sum / pixelCounter;
sum = pixelCounter = 0;
for (int i = 2; i <= 8; i++)
{
int x = right + i;
for (int y = top; y < bottom; y++)
{
sum += GetDepth(depthValue, maxWidth * y + x);
pixelCounter++;
}
}
averDepthRight = sum / pixelCounter;
sum = pixelCounter = 0;
for (int i = -3; i <= 3; i++)
{
int x = (right + left) / 2 + i;
for (int y = top; y < bottom; y++)
{
sum += GetDepth(depthValue, maxWidth * y + x);
pixelCounter++;
}
}
averDepthMiddle = sum / pixelCounter;
//if (averDepthMiddle < averDepthLeft - 20 && averDepthMiddle < averDepthRight - 20)
return(new DetectedDoor(boundingBox, imageSize, confidence, angle, (averDepthLeft + averDepthRight) / 2, DetectedDoor.DetectMethod.DEPTH));
}
public List <DetectedDoor> GetDoors(object data)
{
DFrame depthFrame = data as DFrame;
if (depthFrame == null)
{
return(null);
}
List <DetectedDoor> doors = new List <DetectedDoor>();
//Image<Bgr, Byte> smoothed = img.SmoothGaussian(15);
//Image<Gray, Byte> threshold = FilterColor(smoothed);
//threshold = SimplifyImage(threshold, 100);
// new method
//new method end
using (MemStorage stor = new MemStorage())
{
Bitmap bmp = depthFrame.GetDoorNaviBitmap();
//Bitmap bmp2 = bmp.Clone(new Rectangle(0, 0, bmp.Width, bmp.Height), bmp.PixelFormat);
//Image<Bgr, Byte> img = new Image<Bgr, Byte>(bmp2);
Image <Gray, Byte> grey;
try
{
grey = new Image <Gray, Byte>(bmp);
}
catch (Exception)
{
return(null);
}
//CvInvoke.cvInRangeS(img.Ptr, new MCvScalar(0.0, 0.0, 0.0), new MCvScalar(250.0, 250.0, 250.0), grey.Ptr);
//new method
CvInvoke.cvErode(grey.Ptr, grey.Ptr, (IntPtr)null, 1);
CvInvoke.cvDilate(grey.Ptr, grey.Ptr, (IntPtr)null, 2);
Image <Gray, Byte> cannyEdges = grey.Canny(180, 120);
LineSegment2D[] lines = cannyEdges.HoughLinesBinary(
1, //Distance resolution in pixel-related units
Math.PI / 45.0, //Angle resolution measured in radians.
20, //threshold
5, //min Line width
10 //gap between lines
)[0]; //Get the lines from the first channel
LineSegment2D[] container = null;
container = FilterAndMergeVerticalLines(lines, 1);
container = FilterShortLines(container, 100);
container = FindVerticalDoorFrameLines(container, 500, grey);
if (container != null)
{
int boxX = container[0].P1.X;
int boxY = container[0].P1.Y;
int boxWidth = container[1].P1.X - boxX;
int boxHeight = container[1].P2.Y - boxY;
Rectangle newBox = new Rectangle(boxX, boxY, boxWidth, boxHeight);
int centerX = (newBox.Left + newBox.Right) / 2;
int centerY = (newBox.Bottom + newBox.Top) / 2;
DetectedDoor.DetectionConfidence confidence = GetConfidence(newBox, grey.Size);
int centerXOffset = centerX - (grey.Size.Width / 2);
double angle = -Math.Atan2(-centerY, centerXOffset) - Math.PI / 2;
double distance = GetEstimatedDistance(newBox, grey.Size);
DetectedDoor newDoor = new DetectedDoor(newBox, grey.Size, confidence, angle, distance, DetectedDoor.DetectMethod.DEPTH);
doors.Add(newDoor);
}
//new method end
/** old method
*
* //CvInvoke.cvErode(grey.Ptr, grey.Ptr, (IntPtr)null, 4);
* //CvInvoke.cvDilate(grey.Ptr, grey.Ptr, (IntPtr)null, 2);
*
* //Contour<System.Drawing.Point> contours = grey.FindContours(
* // Emgu.CV.CvEnum.CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_TC89_L1,
* // Emgu.CV.CvEnum.RETR_TYPE.CV_RETR_EXTERNAL);
*
* ////grey = new Image<Gray, byte>(grey.Width, grey.Height, new Gray(0));
* //for (; contours != null; contours = contours.HNext)
* //{
* // Contour<System.Drawing.Point> contour = contours.ApproxPoly(contours.Perimeter * 0.08, stor);
* // if (contour.Area < 80000 && contour.Area > 3000 && contour.Total == 4) //hard code for now, will update later
* // {
* // DetectedDoor newDoor = DoorFromContour(contour, depthFrame.get_DepthData(), grey.Size);
* // if(newDoor != null)
* // doors.Add(newDoor);
* // }
* //}
*
**/
}
return(doors);
}
public List <DetectedDoor> GetDoors(object data)
{
IFrame infraredFrame = data as IFrame;
if (infraredFrame == null)
{
return(null);
}
List <DetectedDoor> doors = new List <DetectedDoor>();
//Image<Bgr, Byte> smoothed = img.SmoothGaussian(15);
//Image<Gray, Byte> threshold = FilterColor(smoothed);
//threshold = SimplifyImage(threshold, 100);
// new method
//new method end
using (MemStorage stor = new MemStorage())
{
Bitmap bmp = infraredFrame.GetBMP();
//Bitmap bmp2 = bmp.Clone(new Rectangle(0, 0, bmp.Width, bmp.Height), bmp.PixelFormat);
//Image<Bgr, Byte> img = new Image<Bgr, Byte>(bmp2);
Image <Gray, Byte> grey;
try
{
grey = new Image <Gray, Byte>(bmp);
}
catch (Exception)
{
return(null);
}
//CvInvoke.cvInRangeS(img.Ptr, new MCvScalar(0.0, 0.0, 0.0), new MCvScalar(250.0, 250.0, 250.0), grey.Ptr);
//new method
CvInvoke.cvErode(grey.Ptr, grey.Ptr, (IntPtr)null, 1);
CvInvoke.cvDilate(grey.Ptr, grey.Ptr, (IntPtr)null, 2);
Image <Gray, Byte> cannyEdges = grey.Canny(180, 120);
LineSegment2D[] lines = cannyEdges.HoughLinesBinary(
1, //Distance resolution in pixel-related units
Math.PI / 45.0, //Angle resolution measured in radians.
20, //threshold
5, //min Line width
10 //gap between lines
)[0]; //Get the lines from the first channel
LineSegment2D[] container = null;
container = FilterAndMergeVerticalLines(lines, 1);
container = FilterShortLines(container, 100);
container = FindVerticalDoorFrameLines(container, 500, grey);
if (container != null)
{
int boxX = container[0].P1.X;
int boxY = container[0].P1.Y;
int boxWidth = container[1].P1.X - boxX;
int boxHeight = container[1].P2.Y - boxY;
Rectangle newBox = new Rectangle(boxX, boxY, boxWidth, boxHeight);
int centerX = (newBox.Left + newBox.Right) / 2;
int centerY = (newBox.Bottom + newBox.Top) / 2;
DetectedDoor.DetectionConfidence confidence = GetConfidence(newBox, grey.Size);
int centerXOffset = centerX - (grey.Size.Width / 2);
double angle = -Math.Atan2(-centerY, centerXOffset) - Math.PI / 2;
DetectedDoor newDoor = new DetectedDoor(newBox, grey.Size, confidence, angle, 0, DetectedDoor.DetectMethod.INFRARED);
doors.Add(newDoor);
}
}
return(doors);
}
