Traffic Signs Recognition Based on PCA-SIFT

被引：0

作者：

Gao Hongwei ^{[1
,2
]}

Liu Chuanyin ^{[2
]}

Yu Yang ^{[2
]}

Li Bin ^{[1
]}

机构：

[1] Chinese Acad Sci, Shenyang Inst Automat, State Key Lab Robot, Beijing, Peoples R China

[2] Shenyang Ligong Univ, Sch Informat Sci & Engn, Shenyang, Peoples R China

来源：

2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2014年

基金：

中国博士后科学基金;

关键词：

Traffic signs; SIFT; PCA-SIFT; Recognition;

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：

Traffic signs automatic recognition was researched in this paper. Traffic signs image preprocessing methods was introduced firstly. Secondly, feature extraction algorithm of traffic signs based on SIFT was elaborated, then a fast SIFT algorithm based on PCA dimensionality reduction was presented to extract the characteristics of traffic signs. Finally, the SVM classifier was studied. A large number of experimental results were completed to demonstrate the effectiveness and practicality of related algorithms.

引用

页码：5070 / 5075

页数：6

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