Automatic Detection of Road Signs for Supporting Car Navigation Data Creation

Yu Aoki, Yoshimitsu Aoki, Emi Miyachi

Research output: Contribution to journalArticle

Abstract

A variety of car navigation systems have been developed for improving convenience of traffic navigation. Regarding construction of maps for car navigation systems, data collection of road navigation signs is necessary. However, the operation for data collection requires so many human tasks and time-consuming. In this paper, we propose a fast and accurate detection method of car navigation signs from videos. First, regions of road navigation signs candidates are extracted by using a color tracking technique robust for illumination changes. Then, the road navigation signs can be detected by applying a shape evaluation to the extracted regions. In order to support actual operations for making car navigation maps, the system automatically judges a best shot from the sequential road sign images by checking their sharpness and sizes. The performance of the system has been evaluated for demonstrating the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)456-464
Number of pages9
JournalJournal of the Institute of Image Electronics Engineers of Japan
Volume36
Issue number4
DOIs
Publication statusPublished - 2007
Externally publishedYes

Fingerprint

Navigation
Railroad cars
Navigation systems
Lighting
Color

Keywords

  • Automatic Detection
  • Best Shot Judgement
  • Color Tracking
  • Road Navigation Sign
  • Shape Evaluation

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Electrical and Electronic Engineering

Cite this

Automatic Detection of Road Signs for Supporting Car Navigation Data Creation. / Aoki, Yu; Aoki, Yoshimitsu; Miyachi, Emi.

In: Journal of the Institute of Image Electronics Engineers of Japan, Vol. 36, No. 4, 2007, p. 456-464.

Research output: Contribution to journalArticle

@article{f1deff12c128468ab52e273aca8093a3,
title = "Automatic Detection of Road Signs for Supporting Car Navigation Data Creation",
abstract = "A variety of car navigation systems have been developed for improving convenience of traffic navigation. Regarding construction of maps for car navigation systems, data collection of road navigation signs is necessary. However, the operation for data collection requires so many human tasks and time-consuming. In this paper, we propose a fast and accurate detection method of car navigation signs from videos. First, regions of road navigation signs candidates are extracted by using a color tracking technique robust for illumination changes. Then, the road navigation signs can be detected by applying a shape evaluation to the extracted regions. In order to support actual operations for making car navigation maps, the system automatically judges a best shot from the sequential road sign images by checking their sharpness and sizes. The performance of the system has been evaluated for demonstrating the effectiveness of the proposed method.",
keywords = "Automatic Detection, Best Shot Judgement, Color Tracking, Road Navigation Sign, Shape Evaluation",
author = "Yu Aoki and Yoshimitsu Aoki and Emi Miyachi",
year = "2007",
doi = "10.11371/iieej.36.456",
language = "English",
volume = "36",
pages = "456--464",
journal = "Journal of the Institute of Image Electronics Engineers of Japan",
issn = "0285-9831",
publisher = "Institute of Image Electronics Engineers of Japan",
number = "4",

}

TY - JOUR

T1 - Automatic Detection of Road Signs for Supporting Car Navigation Data Creation

AU - Aoki, Yu

AU - Aoki, Yoshimitsu

AU - Miyachi, Emi

PY - 2007

Y1 - 2007

N2 - A variety of car navigation systems have been developed for improving convenience of traffic navigation. Regarding construction of maps for car navigation systems, data collection of road navigation signs is necessary. However, the operation for data collection requires so many human tasks and time-consuming. In this paper, we propose a fast and accurate detection method of car navigation signs from videos. First, regions of road navigation signs candidates are extracted by using a color tracking technique robust for illumination changes. Then, the road navigation signs can be detected by applying a shape evaluation to the extracted regions. In order to support actual operations for making car navigation maps, the system automatically judges a best shot from the sequential road sign images by checking their sharpness and sizes. The performance of the system has been evaluated for demonstrating the effectiveness of the proposed method.

AB - A variety of car navigation systems have been developed for improving convenience of traffic navigation. Regarding construction of maps for car navigation systems, data collection of road navigation signs is necessary. However, the operation for data collection requires so many human tasks and time-consuming. In this paper, we propose a fast and accurate detection method of car navigation signs from videos. First, regions of road navigation signs candidates are extracted by using a color tracking technique robust for illumination changes. Then, the road navigation signs can be detected by applying a shape evaluation to the extracted regions. In order to support actual operations for making car navigation maps, the system automatically judges a best shot from the sequential road sign images by checking their sharpness and sizes. The performance of the system has been evaluated for demonstrating the effectiveness of the proposed method.

KW - Automatic Detection

KW - Best Shot Judgement

KW - Color Tracking

KW - Road Navigation Sign

KW - Shape Evaluation

UR - http://www.scopus.com/inward/record.url?scp=85024730680&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85024730680&partnerID=8YFLogxK

U2 - 10.11371/iieej.36.456

DO - 10.11371/iieej.36.456

M3 - Article

AN - SCOPUS:85024730680

VL - 36

SP - 456

EP - 464

JO - Journal of the Institute of Image Electronics Engineers of Japan

JF - Journal of the Institute of Image Electronics Engineers of Japan

SN - 0285-9831

IS - 4

ER -