Traffic Sign Detection in CSharp
Jump to navigation
Jump to search
<font color=green> This project is part of the Emgu.CV.Example solution </font>
System Requirement
| Component | Requirement | Detail |
|---|---|---|
| Emgu CV | Version 2.0.0.0 Alpha | |
| Operation System | Cross Platform |
Traffic Sign Detection
Traffic sign detection is a crucial component in an autonomous vehicle navigation system. For an automobile to navigate itself safely in an urban environment, it must be able to understand traffic signs
- It should be able to read the speed limit, such that it will not received tickets for speeding and paid a premium on its insurance
- It should be able to read traffic lights and stop on red
- It should be able to read stop sign and yield to other vehicles which are also crossing the same intersection.
- ...
This tutorial aims to solve a small part of a autonomous vehicle navigation system, which detect stop sign from images captured by camera.
Stop Sign Detection
The first task to implement a stop sign detection algorithm is to understand the appearance of a stop sign in North American.
A North American stop sign is a red octagon with "STOP" written in the center. Given this information, we design the stop sign detection to be a two pass algorithm:
- In the first step, we try to extract red octagons
- In the second step, we use SURF to match features on the candidate region to our model stop sign. If sufficient matches are found, we consider it a stop sign.
Complete Source code
<source lang="csharp"> using System; using System.Collections.Generic; using System.Text; using System.Drawing; using Emgu.CV; using Emgu.CV.Structure; using Emgu.Util; using System.Diagnostics;
namespace TrafficSignRecognition {
public class StopSignDetector : DisposableObject
{
private SURFTracker _tracker;
private MCvSURFParams _surfParam;
private MemStorage _octagonStorage;
private Contour<Point> _octagon;
public StopSignDetector()
{
_surfParam = new MCvSURFParams(500, false);
using (Image<Bgr, Byte> stopSignModel = new Image<Bgr, Byte>("stop-sign-model.png"))
using (Image<Gray, Byte> redMask = GetRedPixelMask(stopSignModel))
{
_tracker = new SURFTracker(redMask.ExtractSURF(ref _surfParam));
}
_octagonStorage = new MemStorage();
_octagon = new Contour<Point>(_octagonStorage);
_octagon.PushMulti(new Point[] {
new Point(1, 0),
new Point(2, 0),
new Point(3, 1),
new Point(3, 2),
new Point(2, 3),
new Point(1, 3),
new Point(0, 2),
new Point(0, 1)},
Emgu.CV.CvEnum.BACK_OR_FRONT.FRONT);
}
/// <summary>
/// Compute the red pixel mask for the given image.
/// A red pixel is a pixel where: 20 < hue < 160 AND satuation > 10
/// </summary>
/// <param name="image">The color image to find red mask from</param>
/// <returns>The red pixel mask</returns>
private static Image<Gray, Byte> GetRedPixelMask(Image<Bgr, byte> image)
{
using (Image<Hsv, Byte> hsv = image.Convert<Hsv, Byte>())
{
Image<Gray, Byte>[] channels = hsv.Split();
//channels[0] is the mask for hue less than 20 or larger than 160
CvInvoke.cvInRangeS(channels[0], new MCvScalar(20), new MCvScalar(160), channels[0]);
channels[0]._Not();
//channels[1] is the mask for satuation of at least 10, this is mainly used to filter out white pixels
channels[1]._ThresholdBinary(new Gray(10), new Gray(255.0));
CvInvoke.cvAnd(channels[0], channels[1], channels[0], IntPtr.Zero);
channels[1].Dispose();
channels[2].Dispose();
return channels[0];
}
}
private void FindStopSign(Image<Bgr, byte> img, List<Image<Gray, Byte>> stopSignList, List<Rectangle> boxList, Contour<Point> contours)
{
for (; contours != null; contours = contours.HNext)
{
contours.ApproxPoly(contours.Perimeter * 0.02, 0, contours.Storage);
if (contours.Area > 200)
{
double ratio = CvInvoke.cvMatchShapes(_octagon, contours, Emgu.CV.CvEnum.CONTOURS_MATCH_TYPE.CV_CONTOURS_MATCH_I3, 0);
if (ratio > 0.1) //not a good match of contour shape
{
Contour<Point> child = contours.VNext;
if (child != null)
FindStopSign(img, stopSignList, boxList, child);
continue;
}
Rectangle box = contours.BoundingRectangle;
Image<Gray, Byte> candidate;
using (Image<Bgr, Byte> tmp = img.Copy(box))
candidate = tmp.Convert<Gray, byte>();
//set the value of pixels not in the contour region to zero
using (Image<Gray, Byte> mask = new Image<Gray, byte>(box.Size))
{
mask.Draw(contours, new Gray(255), new Gray(255), 0, -1, new Point(-box.X, -box.Y));
double mean = CvInvoke.cvAvg(candidate, mask).v0;
candidate._ThresholdBinary(new Gray(mean), new Gray(255.0));
candidate._Not();
mask._Not();
candidate.SetValue(0, mask);
}
SURFFeature[] features = candidate.ExtractSURF(ref _surfParam);
SURFTracker.MatchedSURFFeature[] matchedFeatures = _tracker.MatchFeature(features, 2, 20);
int goodMatchCount = 0;
foreach (SURFTracker.MatchedSURFFeature ms in matchedFeatures)
if (ms.Distances[0] < 0.5) goodMatchCount++;
if (goodMatchCount >= 10)
{
boxList.Add(box);
stopSignList.Add(candidate);
}
}
}
}
public void DetectStopSign(Image<Bgr, byte> img, List<Image<Gray, Byte>> stopSignList, List<Rectangle> boxList)
{
Image<Bgr, Byte> smoothImg = img.SmoothGaussian(5, 5, 1.5, 1.5);
Image<Gray, Byte> smoothedRedMask = GetRedPixelMask(smoothImg);
smoothedRedMask._Dilate(1);
smoothedRedMask._Erode(1);
using (Image<Gray, Byte> canny = smoothedRedMask.Erode(3).Dilate(3).Canny(new Gray(100), new Gray(50)))
using (MemStorage stor = new MemStorage())
{
Contour<Point> contours = canny.FindContours(
Emgu.CV.CvEnum.CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_SIMPLE,
Emgu.CV.CvEnum.RETR_TYPE.CV_RETR_TREE,
stor);
FindStopSign(img, stopSignList, boxList, contours);
}
}
protected override void DisposeObject()
{
_tracker.Dispose();
_octagonStorage.Dispose();
}
}
} </source>
Result
