基于显著图与傅里叶描述子的交通标志检测  

Traffic Sign Detection Based on Saliency Map and Fourier Descriptor

作　　者：余超超 侯进[1] 侯长征[1] 

机构地区：[1]西南交通大学信息科学与技术学院,成都611756

出　　处：《计算机工程》2017年第5期28-34,共7页Computer Engineering

基　　金：国家自然科学基金面上项目(61371165);成都市科技惠民技术研发项目(2015-HM01-00050-SF);四川省动漫研究中心2015年度科研项目(DM201504)

摘　　要：在交通标志检测过程中,存在标志尺寸变化、旋转失真、投影失真以及部分被遮挡等问题。为此,提出一种基于显著图和傅里叶描述子的交通标志检测算法。采用频率调谐方法得到显著图并将其二值化,初步定位交通标志区域。通过提取区域外层轮廓,利用轮廓周长和长宽比特征滤除干扰信息,对合格轮廓进行凸壳处理,得到归一化凸壳傅里叶描述子,并与标准数据对比得到检测结果。实验结果表明,该算法检测率可达95%以上,同时满足交通标志检测的实时性要求。Aiming at the problems in traffic sign detection process, such as that traffic sign shows dimensional changes, rotation distortion,projection distortion or the sign is partially occluded, in this paper, a traffic sign detection algorithm based on saliency map and Fourier Descriptor（FD） is proposed. Firstly, the Frequency Tuning （FT） method is used to get the saliency map. Second/y, binary operation is utilized on saliency map to achieve binary image and get the regions of traffic sign. By extracting outer contour of the regions, features of contour length and aspect ratio are utilized to filter interference information. Thirdly,the convex hull processing is applied for the eligible contours and FDs of convex hull are extracted and normalized. Finally, detection results are obtained according to the comparison with standard data. Experimental results demonstrate that the detection rate of the proposed algorithm is more than 95% . This algorithm meets the real-time performance requirement of traffic sign detection.

关 键 词：交通标志检测 显著图 轮廓 凸壳 傅里叶描述子 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]