[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.33851/JMIS.2019.6.4.185

Speed Sign Recognition Using Sequential Cascade AdaBoost Classifier with Color Features

Kwon, Oh-Seol (School of Electrical Electronics and Control Eng., Changwon National University)

Publication Information

Journal of Multimedia Information System / v.6, no.4, 2019 , pp. 185-190 More about this Journal

Abstract

For future autonomous cars, it is necessary to recognize various surrounding environments such as lanes, traffic lights, and vehicles. This paper presents a method of speed sign recognition from a single image in automatic driving assistance systems. The detection step with the proposed method emphasizes the color attributes in modified YUV color space because speed sign area is affected by color. The proposed method is further improved by extracting the digits from the highlighted circle region. A sequential cascade AdaBoost classifier is then used in the recognition step for real-time processing. Experimental results show the performance of the proposed algorithm is superior to that of conventional algorithms for various speed signs and real-world conditions.

Keywords

Speed sign recognition; Color features; Sequential cascade Adaboost classifier;

Citations & Related Records

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