山东农业大学学报（自然科学版）2017，Vol.48Issue(3)：400-404,5.DOI:10.3969/j.issn.1000-2324.2017.03.016
基于支持向量机的交通标志人工智能检测与识别
The Intelligent Detection and Recognition for Traffic Signs Based on Support Vector Machine
何诚刚1
作者信息
- 1. 西安交通大学城市学院, 陕西 西安 710018
- 折叠
摘要
Abstract
To solve the problem of low accuracy of intelligent detection and recognition for traffic signs, a fused multi-phase method based on support vector machine theory was put forward for traffic signs detection and identification. Firstly, the histogram of oriented gradient (HOG) was used to extract the feature data of traffic signs. Then the grid search method and cross validation method were applied to search the optimal parameters combination (penalty factor C and kernel parameter r) of the support vector machine model. Finally, the optimal method of support vector machine was applied to identify the traffic signs. Experimental results indicated that the proposed method went up to accuracy 98%of the recognition for traffic signs.关键词
支持向量机/交通标志/智能检测/识别Key words
Support vector machine/traffic signs/intelligent detection/recognition分类
信息技术与安全科学引用本文复制引用
何诚刚..基于支持向量机的交通标志人工智能检测与识别[J].山东农业大学学报（自然科学版）,2017,48(3):400-404,5.
