CAJ | 학술논문

通过变换 RGB 空间颜色值并分割图像,利用标记图为特征的形状分类器检测城市环境中的交通标志.为了提高分类准确度,用两种模型表示方法分类交通标志:1)结合二元树复小波变换和二维独立分量分析提取特征,送入最近邻分类器中分类交通标志;2)提取交通标志的内部图形,利用模板匹配进行分类.最后,将两种分类结果融合输出.实验结果表明,所提出算法的整体识别率超过91%,平均处理帧率达到6.6帧/s,系统能够鲁棒、有效和实时地识别交通标志.
통과변환 RGB 공간안색치병분할도상,이용표기도위특정적형상분류기검측성시배경중적교통표지.위료제고분류준학도,용량충모형표시방법분류교통표지:1)결합이원수복소파변환화이유독립분량분석제취특정,송입최근린분류기중분류교통표지;2)제취교통표지적내부도형,이용모판필배진행분류.최후,장량충분류결과융합수출.실험결과표명,소제출산법적정체식별솔초과91%,평균처리정솔체도6.6정/s,계통능구로봉、유효화실시지식별교통표지.
@@@@The image segmentation based on transforming RGB color space and the shape classifier based on signature feature are used to detect traffic signs in urban scenes. For improving recognition accuracy, two modal representations are presented to classify the traffic sign. 1) The feature of traffic sign is extracted by dual-tree complex wavelet transform(DT-CWT) and 2D independent component analysis(2DICA), then sent to the nearest neighbor classifier to classify traffic sign. 2) The template matching based on intra pictograms of traffic sign is applied to recognition. The recognition results are fused by some decision rules. Experimental results show that, the overall recognition rate of the proposed algorithm is more than 91% and the average frame rate is up to 6.6fps, which indicates that the system is robust, effective and accurate to classify traffic signs.