JOURNAL ARTICLE

Traffic sign detection by template matching based on multi-level chain code histogram

Abstract

This paper proposes a real-time system for traffic signs detection, which features of template matching based on a new feature expression for geometric shapes, namely, multi-level chain code histogram (MCCH). For all of the different shapes associated with Chinese traffic signs, e.g., circle, triangle, inverted triangle and octagon, MCCH is a robust feature expression with remarkable low computational cost, which is particularly important for real-time applications. The proposed system consists of three stages: 1) segmentation based on color; 2) MCCH extraction; 3) template matching. Extensive experiments were conducted using different datasets, demonstrating outstanding performance with regard to high processing speed and accuracy. The system robustness to rotation, scale, and illumination has also been illustrated.

Keywords:
Histogram Chain code Computer science Robustness (evolution) Artificial intelligence Template matching Feature extraction Computer vision Pattern recognition (psychology) Segmentation Matching (statistics) Code (set theory) Histogram of oriented gradients Feature (linguistics) Mathematics Image (mathematics)

Metrics

11
Cited By
1.18
FWCI (Field Weighted Citation Impact)
18
Refs
0.85
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Vehicle License Plate Recognition
Physical Sciences →  Engineering →  Media Technology
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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