Speed Sign Recognition Using Sequential Cascade AdaBoost Classifier with Color Features

Oh-Seol Kwon
2019 Journal of multimedia information system  
An accurate performance was recently reported by Mathias [8] when using a HOG histogram and multi-layer SVM technique based on the distribution of lightness, yet the learning and testing require too much time for real-time processing. A recognition method using cross correlation was also proposed by Barns [9], yet the real-time performance is affected by distortion of the side images. Abstract For future autonomous cars, it is necessary to recognize various surrounding environments such as
more » ... , 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.
doi:10.33851/jmis.2019.6.4.185 fatcat:rxo7gefmrzekdcpvudo4ey6cfu