TY - GEN
T1 - On-road speed sign recognition using fuzzy kernel-based learning vector quantization
AU - Chiang, Hsin Han
AU - Lee, Tsu Tian
AU - Lee, Jian Xun
PY - 2011
Y1 - 2011
N2 - This paper presents an automatic speed sign recognition for providing the visual driving-assistance of speed limits awareness. To reduce the influence of digital noise caused by lighting condition and pollution, a segmentation based on pan-red color information is applied to extract the shape of speed sign. Based on the edge gradient information of a circle shape, a radially symmetry detection strategy is proposed for fast detecting the speed sign candidate from road scenes. The recognition of the content of speed sign is achieved through the fuzzy kernel-based learning vector quantization (FKLVQ) which also verifies each candidate to eliminate non-target blobs. Results show the feasibility and effectiveness of the proposed system under a wide variety of visual conditions.
AB - This paper presents an automatic speed sign recognition for providing the visual driving-assistance of speed limits awareness. To reduce the influence of digital noise caused by lighting condition and pollution, a segmentation based on pan-red color information is applied to extract the shape of speed sign. Based on the edge gradient information of a circle shape, a radially symmetry detection strategy is proposed for fast detecting the speed sign candidate from road scenes. The recognition of the content of speed sign is achieved through the fuzzy kernel-based learning vector quantization (FKLVQ) which also verifies each candidate to eliminate non-target blobs. Results show the feasibility and effectiveness of the proposed system under a wide variety of visual conditions.
KW - Speed sign recognition
KW - color segmentation
KW - fuzzy
KW - learning vector quantization(LVQ)
KW - radial symmetry detection
UR - http://www.scopus.com/inward/record.url?scp=84860403321&partnerID=8YFLogxK
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U2 - 10.1109/ICSSE.2011.5961872
DO - 10.1109/ICSSE.2011.5961872
M3 - Conference contribution
AN - SCOPUS:84860403321
SN - 9781612844718
T3 - Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011
SP - 49
EP - 54
BT - Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011
T2 - 2011 International Conference on System Science and Engineering, ICSSE 2011
Y2 - 8 June 2011 through 10 June 2011
ER -