基于特征点的交通标志识别系统

Kay Thinzar Phu, L. Oo
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引用次数: 4

摘要

特征的选择是图像处理中的一个重要环节。这些重要的特征使其在交通信号识别中获得良好的性能成为可能。本文提出了交通标志识别的重要特征点。道路标志识别一直是一个研究多年的难题。本课题旨在开发实时光照变化下的TSDR系统。该系统提出了RGB颜色阈值检测交通标志,并提出了新的重要特征点(交叉点、终止点和分叉点)。利用自适应神经模糊推理系统(ANFIS)识别特征点。该系统使用缅甸交通标志数据集,在晴天、多云、毛毛雨天气下均能获得较好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traffic sign recognition system using feature points
The selection of features is an important element in image processing. The important features make it possible to obtain good performances in the recognition of traffic signals. This paper presents the significant features points for traffic sign recognition. As a difficult research problem for many years, the recognition of road signs suffers from the different illuminations. The aim of the proposed research is to develop TSDR system under lighting changes in real time. This system proposes RGB color thresholding for traffic signs detection and new significant features points (crossing points, termination point and bifurcation point) are proposed. The features points are recognized with Adaptive Neuro Fuzzy Inference System (ANFIS) system. This system provides good results under sunny, cloudy, drizzle rain weather and uses Myanmar Traffic Sign dataset.
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