TY - GEN
T1 - Illumination invariant color segmentation method based on cluster center tree for traffic sign detection
AU - Woo, Byeongdae
AU - Choi, Yeongwoo
AU - Uh, Youngjung
AU - Lim, Kwangyong
AU - Byun, Hyeran
PY - 2015/1/8
Y1 - 2015/1/8
N2 - This paper proposes a color segmentation method that can locate candidate regions of traffic signs accurately and reliably from real world images. In the real world, there are various light conditions which make the color segmentation very difficult problem. Hence, we propose an illumination invariant color segmentation method. The proposed method consists of two parts; 1) cluster center treebased segmentation 2) illumination estimation. Cluster center tree is trained for color segmentation. Illumination estimation algorithm classifies light condition of the input images. We validate the proposed method qualitatively and quantitatively with 1,745 images containing red and blue traffic signs captured with four light conditions; sunny, cloudy, rainy and night. The proposed method achieves the high detection rate of 99.25% in sunny, 98.33% in cloudy, 87.85% in rainy and 88.70% at night.
AB - This paper proposes a color segmentation method that can locate candidate regions of traffic signs accurately and reliably from real world images. In the real world, there are various light conditions which make the color segmentation very difficult problem. Hence, we propose an illumination invariant color segmentation method. The proposed method consists of two parts; 1) cluster center treebased segmentation 2) illumination estimation. Cluster center tree is trained for color segmentation. Illumination estimation algorithm classifies light condition of the input images. We validate the proposed method qualitatively and quantitatively with 1,745 images containing red and blue traffic signs captured with four light conditions; sunny, cloudy, rainy and night. The proposed method achieves the high detection rate of 99.25% in sunny, 98.33% in cloudy, 87.85% in rainy and 88.70% at night.
UR - http://www.scopus.com/inward/record.url?scp=84926224679&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84926224679&partnerID=8YFLogxK
U2 - 10.1145/2701126.2701139
DO - 10.1145/2701126.2701139
M3 - Conference contribution
AN - SCOPUS:84926224679
T3 - ACM IMCOM 2015 - Proceedings
BT - ACM IMCOM 2015 - Proceedings
PB - Association for Computing Machinery, Inc
T2 - 9th International Conference on Ubiquitous Information Management and Communication, ACM IMCOM 2015
Y2 - 8 January 2015 through 10 January 2015
ER -