Open AccessStudy on Detection and Localization Algorithm of Traffic Signs from Natural Scenes
Author(s) -
Han Xian-Zhong,
Chen Chen,
Wang Ke-Jian,
Yuan Yingchun,
Song Yulong
Publication year - 2014
Publication title -
advances in mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 40
ISSN - 1687-8132
DOI - 10.1155/2014/318635
Subject(s) - traffic sign , computer vision , artificial intelligence , computer science , feature (linguistics) , affine transformation , distortion (music) , segmentation , intelligent transportation system , sign (mathematics) , color constancy , transformation (genetics) , pattern recognition (psychology) , algorithm , image (mathematics) , engineering , mathematics , mathematical analysis , amplifier , linguistics , philosophy , computer network , civil engineering , biochemistry , chemistry , bandwidth (computing) , pure mathematics , gene
Automatic detection and location of traffic signs is an important part of intelligent transportation, especially for unmanned vehicle technology research. For the morphological feature of China road traffic signs, we propose a traffic sign detection method based on color segmentation and shape analysis. Firstly, in order to solve the problems of traffic signs color cast, distortion, and cross-color in natural scenes, the images are processed by white balance, Retinex color enhancement, and affine transformation. Then, the type of traffic signs is discriminated and detected, according to the color and shape characteristics of traffic signs. The experimental results show that this method can effectively detect and recognize traffic signs.
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