[1]罗艳,蔡自兴.指示类交通标识的自动检测[J].智能系统学报,2011,6(3):213-218.
LUO Yan,CAI Zixing.Automatic detection of indicative traffic signs[J].CAAI Transactions on Intelligent Systems,2011,6(3):213-218.
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LUO Yan,CAI Zixing.Automatic detection of indicative traffic signs[J].CAAI Transactions on Intelligent Systems,2011,6(3):213-218.
指示类交通标识的自动检测
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
6
期数:
2011年第3期
页码:
213-218
栏目:
学术论文—机器感知与模式识别
出版日期:
2011-06-25
- Title:
- Automatic detection of indicative traffic signs
- 文章编号:
- 1673-4785(2011)03-0213-06
- Keywords:
- indicative traffic signs; HSV color search; circularity; corner detection; distance histogram
- 分类号:
- TP391.4
- 文献标志码:
- A
- 摘要:
- 针对指示类交通标识的特点，进行标志牌检测算法的研究.首先利用快速HSV颜色查找的方法进行颜色分割，对颜色分割后的二值图进行必要的形态学预处理，接着利用圆形度和拐角检测与几何特征结合的方法进行形状识别.针对某些圆形标志边缘分割不完整的情形，提出一种根据距离直方图判断是否为圆形标志的方法.实验结果表明，算法对实际道路环境下的指示类交通标识的检测具有较好准确性和鲁棒性，满足实时性要求.
- Abstract:
- This paper studied the detection algorithms of indicative traffic signs. First, the color segmentation was recorded along with a fast HSV color search method, and later the morphologic preprocessing was taken on the binary image after the color segmentation. Second, circularity and corner detection combined with geometric characteristics were used to judge if a region was an indicative sign. Last, in view of the incomplete edge of the round sign after the color segmentation, a new algorithm was raised based on a distance histogram for confirmation. Experimental results show that this algorithm is accurate and robust for detecting indicative traffic signs in real traffic environments, and also meets the realtime demand.
- 参考文献/References:
-
［1］张宵，彭维.基于Hough变换的圆形物体的检测［J］.传感器与微系统， 2006, 25(4): 6264.
ZHANG Xiao, PENG Wei. Detection of circle based on Hough transform［J］. Transducer and Microsystem Technologies, 2006, 25(4): 6264.
［2］许少秋.户外交通标识检测和形状识别［J］.中国图象图形学报， 2009, 14(4): 707711.
?XU Shaoqiu. Traffic sign detection and shape recognition in outdoor environments［J］. Journal of Image and Graphics, 2009, 14(4): 707711.
［3］HSU S H, HUANG C L. Road sign detection and recognition using matching pursuit method［J］. Image and Vision Computing, 2001, 19(3): 119129.
［4］胡小燕.基于小波神经网络的交通标识识别研究［D］.上海：华东交通大学, 2006: 4248.
HU Xiaoyan. Traffic signs recognition research based on wavelet neural network［D］. Shanghai: East China Jiaotong University, 2006: 4248.
［5］De LA ESCALERA A, MORENO L, SALICHS M A, et al. Road traffic sign detection and classification［J］. IEEE Transactions on Industrial Electronics, 1997, 44(6): 848859.
［6］De LA ESCALERA A, ARMINGOJ J M, MATA M. Traffic sign recognition and analysis for intelligent vehicles［J］. Image and Vision Computing, 2003, 21(3): 247258.
［7］刘旭东.高速公路限速标志检测与识别技术研究［D］.福州：福建农业大学, 2009: 3234.
?LIU Xudong. Study on the technique of motorway speed limit sign detection and recognition［D］.Fuzhou: Agricultural University of Fujian, 2009: 3234.
［8］陈维馨.道路交通标识检测技术研究［D］.厦门：厦门大学, 2007: 1418.
CHEN Weixin. Road traffic sign detection［D］. Xiamen: Xiamen University, 2007: 1418.
［9］黄志勇,孙光民,李芳.基于RGB视觉模型的交通标识分割［J］.微电子与计算机技术, 2004, 21（10）: 147152.
HUANG Zhiyong, SUN Guangming, LI Fang. Traffic sign segment based on RGB vision model［J］. Microelectronics and Computer, 2004, 21(10): 147152.
［10］HIROSE K, ASAKURA T, AOYAGI Y. Realtime recognition of road traffic sign in moving scene image using new image filter［C］//The 26th Annual Conference of the IEEE Industrial Electronics Society. Nagoya, Japan, 2000: 1318.
备注/Memo
收稿日期： 2010-12-22.
基金项目：国家自然科学基金资助项目(90820302).
通信作者：罗艳.E-mail:luoyan0702@sohu.com.
作者简介：
罗艳，女，1984年生，硕士研究生，主要研究方向为图像处理与机器视觉.
蔡自兴，男，1938年生，教授，博士生导师，国际导航与运动控制科学院院士，纽约科学院院士，首届全国高校国家级教学名师.主要研究方向为智能系统、人工智能、智能控制、机器人等.主持并完成国家级和省部级科教研究项目30余项，此外，还主持国家级精品课程、国家级教学团队和全国双语教学示范课程等项目，获得国际奖励2项、国家级奖励2项、省部级以上奖励12项.发表学术论文800余篇，出版专著、教材31部.
更新日期/Last Update:
2011-07-23