Video-based detection and classification of US traffic signs and mile markers using color candidate extraction and feature-based recognition

Vahid Balali, Mani Golparvar-Fard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Traffic sign and mile-marker detection and classification are among the important components of highway asset management systems. The significant number of these high-quantity and low-cost assets in US highways can negatively impact the quality of any manual data collection and analysis. To address these challenges, this paper presents an efficient pipeline for video-based detection and classification of traffic signs and mile-markers based on color and shape criteria. Candidate extraction is based on finding the optimum RGB thresholds which yield high detection rates (very low false-negatives) while keeping the number of false-positives in check. The connected components from a thresholded image are extracted next. We use sliding windows, Haar-like features, and the AdaBoost learning method to classify the detected assets. Experimental results with an average classification accuracy of 79.30% on actual data collected from US-460 highway show the promise of the proposed method for reducing the time and effort required for developing traffic road asset inventories.

Original languageEnglish (US)
Title of host publicationComputing in Civil and Building Engineering - Proceedings of the 2014 International Conference on Computing in Civil and Building Engineering
EditorsR. Raymond Issa, Ian Flood
PublisherAmerican Society of Civil Engineers
Pages858-866
Number of pages9
ISBN (Electronic)9780784413616
DOIs
StatePublished - Jan 1 2014
Event2014 International Conference on Computing in Civil and Building Engineering - Orlando, United States
Duration: Jun 23 2014Jun 25 2014

Publication series

NameComputing in Civil and Building Engineering - Proceedings of the 2014 International Conference on Computing in Civil and Building Engineering

Other

Other2014 International Conference on Computing in Civil and Building Engineering
Country/TerritoryUnited States
CityOrlando
Period6/23/146/25/14

ASJC Scopus subject areas

  • Computer Science Applications
  • Civil and Structural Engineering
  • Building and Construction

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