A novel approach of road recognition based on deformable template and genetic algorithm

被引：0
|
作者：
Liu, T [1 ]
Zheng, NN [1 ]
Cheng, H [1 ]
Xing, ZB [1 ]
机构：
[1] Xian Jiaotong Univ, Inst Intelligence & Robot, Xian 710049, Peoples R China
来源：
2003 IEEE INTELLIGENT TRANSPORTATION SYSTEMS PROCEEDINGS, VOLS. 1 & 2 | 2003年
关键词：
road recognition; deformable template; likelihood function; genetic algorithm;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Road recognition based on vision navigation is an important task in intelligent vehicle research. Road image is usually influenced by shadows, noise and discontinuity of road contour, and this induces the traditional edge-based algorithm's robustness decrease greatly. To avoid negative influence from threshold selection, this paper presents a deformable template and genetic algorithm based road recognition algorithm. Firstly, preprocess road image with edge operator to get the edge information, then construct a deformable template model of road contour and its likelihood function which define the fitting degree for a given template deformable parameter, finally genetic algorithm is used to search the global maximal value of the likelihood function to get the optimal parameter of the deformable template model of road contour. Experimental results indicate that the algorithm has strong robustness for shadows, noise and discontinuity of road contour.
引用
收藏
页码：1251 / 1256
页数：6
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