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Traffic sign recognition without color information
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0002-1429-2345
2015 (English)In: Colour and Visual Computing Symposium (CVCS), 2015 / [ed] Pedersen, M; Thomas, JB, IEEE conference proceedings, 2015, 1-6 p.Conference paper (Refereed)
Abstract [en]

Color represents an important attribute in the field of traffic sign recognition. However, when the color of the traffic sign fades or the traffic scene is collected in gray as in the case of Infrared imaging, then color based recognition systems fail. Other problems related to color are simply that different countries use different colors. Even within the European Union, colors of traffic signs are not the same. This paper aims to present a new approach to detect traffic signs without color attributes. It is based a two-stage sliding window which detects traffic signs in the multi-scale image. Histogram of Oriented Gradients HOG descriptors are computed as a quality function which are evaluated by two SVM classifier; the coarse and the fine detectors. Different objects detected by the coarse detectors are clustered and a fine search is conducted in the areas where traffic signs are more probable to exist. Experiments conducted to detect traffic signs under different light conditions such as sunny, cloudy, fog and snow fall have showed a performance of 98% and very low false positive rate. The proposed approach was tested on the Yield traffic signs because it has a simple triangular shape which can be found in many places other than the traffic signs which represent a challenge to the proposed approach.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. 1-6 p.
Keyword [en]
Traffic sign Recognition, SVM, HOG descriptors, Classification, Multi-scale images
National Category
Signal Processing
Research subject
Complex Systems – Microdata Analysis
Identifiers
URN: urn:nbn:se:du-21032DOI: 10.1109/CVCS.2015.7274886ISI: 000380410200009OAI: oai:DiVA.org:du-21032DiVA: diva2:902907
Conference
Colour and Visual Computing Symposium (CVCS), 2015, Gjovik, 25-26 Aug. 2015
Available from: 2016-02-12 Created: 2016-02-12 Last updated: 2016-08-19Bibliographically approved

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Fleyeh, Hasan
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