计算机科学 ›› 2010, Vol. 37 ›› Issue (11): 287-288.

• 图形图像 • 上一篇    下一篇

基于二维主成分分析的交通标志牌识别

唐琎,刘波,蔡自兴,谢斌   

  1. (中南大学信息科学与工程学院 长沙410075)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金重大研究计划重点项目(90820302)资助。

Traffic Sign Recognition Based on Two-dimensional Principal Component Analysis

TANG Jin,LIU Bo,CAI Zi-xing,XIE Bin   

  • Online:2018-12-01 Published:2018-12-01

摘要: 提出了将二维主成分分析方法应用于交通标志牌识别的特征提取,并在已建立的两个标志牌的数据库上利用最近部分类器与欧氏距离度量进行了相应的实验。一个数据库是将标志牌图像二值化后经过一系列的仿真变换得到的,另外一个数据库是选取不同位置场景经过实地拍摄得到的标志牌图像。本方法对两个图像库的识别都得到了良好的效果。

关键词: 模式识别,交通标志识别,二维主成分分析,特征提取

Abstract: This paper proposed a feature extraction method for traffic sign recognition based on Two-Dimensional Principal Component Analysis (2DPCA). A series of experiments were performed on two traffic sign databases with the nearest neighbor classifier and Euler distance. One database is the image library in which images are obtained through a series of simulation transformation after image binarization, While another database is made up of images shot from real scenes through selecting many different location scenes. The method has a good effect on the recognition of the both image databases.

Key words: Pattern recognition,Traffic sign recognition, 2DPCA, Feature extraction

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