DocumentCode :
233713
Title :
Background pixels mutation detection and Hu invariant moments based traffic signs detection on autonomous vehicles
Author :
Fu Meng-Yin ; Liu Fang-yu ; Yang Yi ; Wang Mei-ling
Author_Institution :
Beijing Inst. of Technol., Beijing, China
fYear :
2014
fDate :
28-30 July 2014
Firstpage :
670
Lastpage :
674
Abstract :
In this paper, background pixels mutation detection and Hu invariant moments based traffic signs segmentation are combined in traffic signs detection. Considering the gray histogram information in S space, it has good segmentation effects as a global threshold selection method, which can greatly reduce the processing time of the subsequent work. Then using moment invariant theory to extract standard images and seven Hu invariant moments of traffic signs, we contrast the eigenvalues with the suspected areas to establish a rapid and reliable traffic signs detection method.
Keywords :
feature extraction; image segmentation; intelligent transportation systems; object detection; statistical analysis; traffic engineering computing; Hu invariant moments; background pixels mutation detection; global threshold selection method; gray histogram information; image extraction; segmentation effect; traffic sign detection; Eigenvalues and eigenfunctions; Feature extraction; Gray-scale; Histograms; Image color analysis; Image segmentation; Standards; Background pixels mutation detection; Eigenvalues extraction; Hu invariant moments; Traffic signs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2014 33rd Chinese
Conference_Location :
Nanjing
Type :
conf
DOI :
10.1109/ChiCC.2014.6896705
Filename :
6896705
Link To Document :
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