Table 1 Comparison of traffic sign detection algorithms.
From: YOLO-BS: a traffic sign detection algorithm based on YOLOv8
Method | Algorithms | Advantages | Disadvantages |
|---|---|---|---|
Traditional methods | Algorithms based on colors or shapes | Simple to implement, low computational resources | Sensitive to complex backgrounds and lighting changes |
Machine learning | HOG, SIFT, SVM, RF | Require less data compared to deep learning methods | poor accuracy, time-consuming |
Deep learning | CNN | Automatically extracts features, high accuracy | Requires a significant amount of labeled data for training |
Faster R-CNN | High accuracy, particularly for small objects | Higher computational and time costs | |
SSD, YOLO | Fast speed with relatively high accuracy | Poor performance on small object detection |
