基于径向对称变换的自适应交通禁止标志检测

提出一种基于径向对称变换的自适应交通禁止标志的检测算法。采用RGB归一化阈值分割算法对交通图像进行二值化处理,构造和利用区域轮廓特征矢量,判决和提取候选标志区域。对于标志互相遮挡候选区域,提出采用基于分水岭变换的自适应标志分离算法进行标志分离;然后,对于低维的标志候选区域,根据其自身尺度特征提出一种参数自适应的径向对称圆形检测器和检测算法,最终确定禁止标志。本文算法在标准交通标志数据集(GTSDB)进行了实验验证。实验结果表明,与现有方法相比,本文算法有效提高了算法执行效率和检测性能,降低了算法复杂度;并且,对交通标志尺度、亮度和天气变化、运动模糊以及标志互相遮挡等有着良好的鲁棒性。

Adaptive traffic prohibitive sign detection based on radial symmetry transform

Traffic sign detection is a key technology in driving assistance syste ms.The effective detection for prohibitive signs is crucial to ensure the driver safety and reduce the traffic accidence.In this paper,we propose an adaptive detection method for prohibitive signs based on the radial symmetry transform.A traffic image is segmented based on RGB normalized threshold algorithm and a binary image is gene rated.Then a regional contour feature vector is constructed and used to determine and extract every ca ndidate sign region.For the region with possible mutually occluding signs,an adaptive separation algorithm based on the watershed transform is presented to perform signs separation.For each abstracted cand idate sign region,the key parameters in the radial symmetry transform are set adaptively according to the scale feature of the region,and an adaptive radial symmetry circular detector and corresponding detection approa ch are constructed and used to detect the prohibitive signs and reject the non-sign regions.The performance of the propo sed method is tested on the German traffic sign detection benchmark (GTSDB).Experimental results demonstrate the effectiveness of our method.Our method outperforms the existing algorithms in terms of execution effi ciency,detection rate and algorithm complexity,and ours has the robustness to th e object scale variation,variable lighting condition and weather,motion blurring and mutual occlusion of signs,etc.