Automatic understanding of road signs in vehicular active night vision system

Oded Perry, Yitzhak Yitzhaky

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes a supplemental mechanism to active vehicular night vision systems, which automatically identifies and reads road signs through image processing. This may add important driving aid in difficult night situations where signs can be missed or when the language is not clear to the driver. Such a solution poses a challenge, as the night vision systems produce low-resolution images with intensity flaws. To examine the validity of the proposed sign and character recognition method, we examined available samples from three classes of road sign information: English letters, Hebrew letters and traffic symbols. The obtained feature separation results show the potential of full implementation in vehicular night vision systems.

Original languageAmerican English
Title of host publicationICALIP 2012 - 2012 International Conference on Audio, Language and Image Processing, Proceedings
Pages7-13
Number of pages7
DOIs
StatePublished - 1 Dec 2012
Event2012 3rd IEEE/IET International Conference on Audio, Language and Image Processing, ICALIP 2012 - Shanghai, China
Duration: 16 Jul 201218 Jul 2012

Publication series

NameICALIP 2012 - 2012 International Conference on Audio, Language and Image Processing, Proceedings

Conference

Conference2012 3rd IEEE/IET International Conference on Audio, Language and Image Processing, ICALIP 2012
Country/TerritoryChina
CityShanghai
Period16/07/1218/07/12

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Computer Vision and Pattern Recognition

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