# Vision-Based Traffic Sign Detection and Recognition Systems: Current Trends and Challenges
## 4 Traffic Sign Detection, Tracking and Classification Methods  
As aforementioned, a TSDR is a driver supportive system that can be used to notify and warn the driver in adverse conditions. This system is a vision-based system that usually has the capability to detect and recognize all traffic signs, even those signs that may be partially occluded or somewhat distorted [14]. Its main tasks are locating the sign, identifying it and distinguishing one sign from another [15; 16]. Thus, the procedure of the TSDR system can be divided into three stages, the detection, tracking and classification stages. Detection is concerned with locating traffic signs in the input scene images, whereas classification is about determining what type of sign the system is looking at [17; 18]. In other words, traffic sign detection involves generating candidate region of interests (ROIs) that are likely to contain regions of traffic signs, while traffic sign classification gets each candidate ROI and tries to identify the exact type of sign or rejects the identified ROI as a false detection [4; 19]. Detection and \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Dataset** & **Country** & **Classes** & \begin{tabular}{c} **TS** \\ **Scenes** \\ \end{tabular} & **TS Images** & **Image Size (px)** & **Sign Size (px)** & **Include Videos** \\ \hline \begin{tabular}{c} **GTSDB** \\ **(2012 and 2013)** \\ \end{tabular} & Germany & 43 & 9000 & 39,209 (training) & \(15\times 15\) to \(250\times 250\) & \(15\times 15\) to \(250\times 250\) & No \\ \hline \begin{tabular}{c} **KULD** \\ **(2009)** \\ \end{tabular} & Belgium & 100+ & 9006 & 13,444 & 1628 \(\times\) 1236 & \(100\times 100\) to \(1628\times 1236\) & Yes, 4 tracks \\ \hline \begin{tabular}{c} **STSD** \\ **(2011)** \\ \end{tabular} & Sweden & 7 & 20,000 & 3488 & 1280 \(\times\) 960 & \(3\times 5\) to \(263\times 248\) & No \\ \hline \begin{tabular}{c} **RUCD** \\ **(2003)** \\ \end{tabular} & \begin{tabular}{c} The \\ Netherlands \\ \end{tabular} & 3 & 48 & 48 & 360 \(\times\) 270 & N/A & No \\ \hline \begin{tabular}{c} **Steropolis** \\ **(2010)** \\ \end{tabular} & France & 10 & 847 & 251 & 1920 \(\times\) 1080 & \(25\times 25\) to \(204\times 159\) & No \\ \hline \begin{tabular}{c} **LISAD** \\ **(2012)** \\ \end{tabular} & US & 49 & 6610 & 7855 & 640 \(\times\) 480 & 1024 \(\times\) 52 & \(6\times 6\) to \(167\times 168\) & All annotations \\ \hline \begin{tabular}{c} **UKOD** \\ **(2012)** \\ \end{tabular} & UK & 100+ & 43,509 & 1200 (synthetic) & 648 \(\times\) 480 & 24 \(\times\) 24 & No \\ \hline \
\begin{tabular}{c} **RTSD** \\ **(2013)** \\ \end{tabular} & Russia & 140 & N/A &
\begin{tabular}{c} 80,000+ \\ (synthetic) \\ \end{tabular} & 1280 \(\times\) 720 & 30 \(\times\) 30 & No \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Publicly available traffic sign databases [13]. Figure 5: Examples of traffic scenes in the German Traffic Signs Detection Benchmark (GTSDB) database [12]. classification usually constitute recognition in the scientific literature. Figure 6 illustrates the main stages of the traffic sign recognition system. As indicated in the figure, the system is able to work in two modes, the training mode in which a database can be built by collecting a set of traffic signs for training and validation, and a testing mode in which the system can recognize a traffic sign which has not been seen before. In the training mode, a traffic sign image is collected by the camera and stored in the raw image database to be classified and used for training the system. The collected image is then sent to color segmentation process where all background objects and unimportant information in the image are eliminated. The generated image from this step is a binary image containing the traffic sign and any other objects similar to the color of the traffic sign. The noise and small objects in the binary image are cleaned by the object selector process and the generated image is then used to create or update the training image database.