An Efficient Real Time Rectangle Speed Limit Sign Recognition System

被引：1

作者：

Zhang Yankun ^{[1
]}

Hong Chuyang ^{[1
]}

Charles Wang ^{[1
]}

机构：

[1] Harman Internal Natl, Shanghai RD Ctr, Corp Tech Grp, Shanghai 200233, Peoples R China

来源：

2010 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV) | 2010年

关键词：

CLASSIFICATION;

D O I：

10.1109/ICOSP.2010.5656721

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper present an efficient real time rectangle speed limit sign recognition system. The system design considers computation load and hardware resources for driver assistant system. First multi-scale overlapping LBP features are used to train AdaBoost cascade classifier for speed limit sign object detection. Then a simple linear prediction method is used to do tracking task. At the recognition stage, a novel efficient algorithm is used to correct rotation angle, and then integral image based adaptive threshold algorithm is adopted to segment the speed limit number. The clustering based binary tree of linear support vector machine is adopted for classification task. The system is tested on real road scene video sequences. It achieves 98.3% recognition rate with approximate 16fps frame rate on laptop.

引用

页码：34 / 38

页数：5

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