# Vision-Based Traffic Sign Detection and Recognition Systems: Current Trends and Challenges
## 4 Traffic Sign Detection, Tracking and Classification Methods
### Detection Phase
#### 4.1.2 Shape-Based Methods  
Just as traffic signs have specific colors, they also have very well-defined shapes that can be searched for. Shape-based methods ignore the color in favor of the characteristic shape of signs [17]. Detection of a traffic sign via its shape follows the defining algorithm of shape detection i.e., to finding the contours and approximating it to reach a final decision based on the number of contours [15; 23]. Shape detection is preferred for traffic signs recognition as the colors found on traffic signs changes according to illumination. In addition, shape detection reduces the search for a road sign regions \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Techniques** & **Paper** & **Segmentation Methods** & **Advantages** & **Sign Type** & **No. of Test** & **Test Image** \\ \hline
**Color** & [7] & RGB color segmentation & Simple & Any color & 2000 & N/A \\
**Thresholding** & [38] & RGB color segmentation with enhancement of color & Fast and high detection rate & Red, blue, yellow & 135 & Video data \\ \hline  & [40] & HSI thresholding with addition for white signs & Segments adversely illuminated signs & Any color & N/A & High-res \\ \cline{2-7}  & [33] & HSI color-based segmentation & Simple and fast & Any color & N/A & N/A \\ \cline{2-7}
**HS(HSV)** & [41] & RGB to HSI transformation & Segments adversely illuminated signs & Any color & N/A & Low-res \\ \cline{2-7}  & [42] & RGB to HSI transformation & N/A & Red & N/A & Low-res \\ \cline{2-7}  & [43] & RGB to HSI transformation & N/A & Any color & 3028 & Low-res \\ \cline{2-7}  & [44] & HSI color-based segmentation & Simple and high accuracy rate & Red, blue & N/A & Video data \\ \cline{2-7}  & [45] & HSI color-based segmentation & Simple and real time application & Any color & 632 & High-res \\ \hline
**Region Growing** & [48] & Started with seed and expand to grey pixels with similar affinity & N/A & N/A & N/A & N/A \\ \cline{2-7}  & [47] & Comparison of two any-color images is done by comparing their & Straightforward, fast method & Any color & N/A & Low-res \\ \hline
**Color Indexing** & [50] & Color histogram & Straightforward, fast & Any color & N/A & N/A \\ \cline{2-7}  & [49] & Color histogram & Straightforward, fast & Any color & N/A & N/A \\ \hline
**Dynamic Pixel** & [52] & Dynamic threshold in pixel aggregation on HSV color space & True method & Any color & 620 & Low-res \\ \hline
**CIECAM97** & [54] & RGB to CIE XYZ transformation, then to LCFI space using CIECAM97 model & Invariant in different lighting conditions & Red, blue & N/A & N/A \\ \hline
**YCbCr Color** & [55] & RGB to YCbCr transformation then dynamic thresholding is performed in Cr component to extract red object & Simple and high accuracy & Red & 193 & N/A \\ \cline{2-7}  & [56] & RGB to extract red object & High accuracy less processing time & Any color & N/A & Low-res \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Colors based approaches for TSDR system. from the whole image to a small number of pixels [57]. However, for this method the memory and computational requirement is quite high for large images [58]. In addition, damaged, partially obscured, faded and blurred traffic signs may cause difficulties in detecting traffic signs accurately, leading to a low accuracy rate. Detection of the traffic signs in these methods is made from the edges of the image analyzed by structural or comprehensive approaches [23]. Many shape-based methods are popular in TSDR systems. These methods are represented in Figure 10 and reviewed respectively in Table 4.  
The most common shape-based approach is the Hough transformation. The Hough transformation usually isolates features of a particular shape within a given frame/images [15]. It was applied by [PERSON] et al. in [59] to detect triangular and circular signs. Their own test datasets contained 14,763 and 1584 signs, and the accuracy rate was approximately 90%.