Multi-stage with neuro-fuzzy approach for efficient on-road speed sign detection and recognition

Hsin Han Chiang, Yen Lin Chen*, Tsu Tian Lee

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

6 引文 斯高帕斯(Scopus)

摘要

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.

原文英語
頁(從 - 到)2919-2939
頁數21
期刊International Journal of Innovative Computing, Information and Control
9
發行號7
出版狀態已發佈 - 2013
對外發佈

ASJC Scopus subject areas

  • 軟體
  • 理論電腦科學
  • 資訊系統
  • 計算機理論與數學

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