Real-time road lane recognition using fuzzy reasoning for AGV vision system

被引：6

作者：

Kuang, P ^{[1
]}

Zhu, QX ^{[1
]}

Liu, GC ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Coll Comp Sci & Technol, Chengdu 610054, Peoples R China

来源：

2004 INTERNATIONAL CONFERENCE ON COMMUNICATION, CIRCUITS, AND SYSTEMS, VOLS 1 AND 2: VOL 1: COMMUNICATION THEORY AND SYSTEMS - VOL 2: SIGNAL PROCESSING, CIRCUITS AND SYSTEMS | 2004年

关键词：

road lane recognition; fuzzy reasoning; Hough transform; real-time; AGV; computer vision;

D O I：

10.1109/ICCCAS.2004.1346345

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Automatic guided vehicles (AGV) vision system is an important research area in computer vision. In order to recognize the road lane quickly and effectively, this paper presented a algorithm using Fuzzy reasoning based on Hough transform to solve this problem, which improves the entire system's real-time performance. After our tests on the test vehicle, this method can speed up the road lane recognition velocity phenomenally, and it also can improve the stability in driving.

引用

页码：989 / 993

页数：5

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