Abstract
This paper presents an automatic speed sign recognition system to provide speed limit awareness functions for driver assistance. To reduce the influence of digital noise caused by ambient lighting conditions and sign pollutions, an efficient segmentation method based on pan-red color information was applied to extracting the shape of a speed sign. Based on the edge gradient information of a circular shape, a radial symmetry detection strategy is proposed for fast detection of the speed sign candidates from various urban road scenes. The recognition of the information of a speed sign is achieved through the proposed fuzzy adaptive-kernel-based learning vector quantization (FAKLVQ) approach, which also verifies each candidate to eliminate non-target blobs. Experiments demonstrated the feasibility and effectiveness of the proposed system under a wide variety of outdoor conditions.
| Original language | English |
|---|---|
| Pages (from-to) | 2919-2939 |
| Number of pages | 21 |
| Journal | International Journal of Innovative Computing, Information and Control |
| Volume | 9 |
| Issue number | 7 |
| Publication status | Published - 2013 |
| Externally published | Yes |
Keywords
- Color segmentation
- Fuzzy
- Learning vector quantization (LVQ)
- Radial symmetry detection
- Speed sign recognition
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
- Information Systems
- Computational Theory and Mathematics