Traffic Sign Detection in CSharp

This project is part of the Emgu.CV.Example solution

System Requirement

Component	Requirement	Detail
Emgu CV	Version 2.4.0
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.

North American Stop Sign

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

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Drawing;
using System.Text;
using Emgu.CV;
using Emgu.CV.Features2D;
using Emgu.CV.Structure;
using Emgu.Util;

namespace TrafficSignRecognition
{
   public class StopSignDetector : DisposableObject
   {
      private Features2DTracker<float> _tracker;
      private SURFDetector _detector;
      private MemStorage _octagonStorage;
      private Contour<Point> _octagon;

      public StopSignDetector(Image<Bgr, Byte> stopSignModel)
      {
         _detector = new SURFDetector(500, false);
         using (Image<Gray, Byte> redMask = GetRedPixelMask(stopSignModel))
         {
            _tracker = new Features2DTracker<float>(_detector.DetectFeatures(redMask, null));  
         }
         _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 &lt; hue &lt; 160 AND satuation &gt; 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();

            try
            {
               //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);
            }
            finally
            {
               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);
               }

               ImageFeature<float>[] features = _detector.DetectFeatures(candidate, null);

               Features2DTracker<float>.MatchedImageFeature[] matchedFeatures = _tracker.MatchFeature(features, 2);

               int goodMatchCount = 0;
               foreach (Features2DTracker<float>.MatchedImageFeature ms in matchedFeatures)
                  if (ms.SimilarFeatures[0].Distance < 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);

         //Use Dilate followed by Erode to eliminate small gaps in some countour.
         smoothedRedMask._Dilate(1);
         smoothedRedMask._Erode(1);

         using (Image<Gray, Byte> canny = smoothedRedMask.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();
      }
   }
}

Result

• Windows

• Android (Nexus S)