Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 164

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Real-Time Speed Sign Detection Using the Radial Symmetry Detector

Barnes, N., Zelinsky, A., Fletcher, L.S.·2008·IEEE Transactions on Intelligent Transportation Systems

Abstract

Algorithms for classifying road signs have a high computational cost per pixel processed. A detection stage that has a lower computational cost can facilitate real-time processing. Various authors have used shape and color-based detectors. Shape-based detectors have an advantage under variable lighting conditions and sign deterioration that, although the apparent color may change, the shape is preserved. In this paper, we present the radial symmetry detector for detecting speed signs. We evaluate the detector itself in a system that is mounted within a road vehicle. We also evaluate its performance that is integrated with classification over a series of sequences from roads around Canberra and demonstrate it while running online in our road vehicle. We show that it can detect signs with high reliability in real time. We examine the internal parameters of the algorithm to adapt it to road sign detection. We demonstrate the stability of the system under the variation of these parameters and show computational speed gains through their tuning. The detector is demonstrated to work under a wide variety of visual conditions.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/tits.2008.922935

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Cited by

See all 164

Metadata

Authors
Barnes, N., Zelinsky, A., & Fletcher, L. S.
Venue
IEEE Transactions on Intelligent Transportation Systems
Published
2008-06
Volume
9
Issue
2
Pages
322-332
ISSN
  • 1524-9050 (ISSN-L)
  • 1558-0016
OpenAlex
W2131171972
Cited by
164
References
2
FWCI
19.71
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Real-Time Speed Sign Detection Using the Radial Symmetry Detector. https://app.cochat.ai/papers/10.1109/tits.2008.922935
The paper
Barnes, N., Zelinsky, A., & Fletcher, L. S. (2008). Real-Time Speed Sign Detection Using the Radial Symmetry Detector. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/tits.2008.922935

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.