A fast method to detect and recognize scaled and skewed road signs

Yi Sheng Liou*, Der Jyh Duh, Shu Yuan Chen, Jun-Wei Hsieh

*Corresponding author for this work

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

1 Scopus citations

Abstract

A fast method to detect and recognize scaled and skewed road signs is proposed in this paper. The input color image is first quantized in HSV color model. Border tracing those regions with the same colors as road signs is adopted to find the regions of interest (ROI). Verification is then performed to find those ROIs satisfying specific constraints as road sign candidates. The candidate regions are extracted and normalization is automatically calculated to handle scaled and skewed road signs. Finally, matching based on distance maps is adopted to measure the similarity between the scene and model road signs to accomplish recognition. Experimental results show that the proposed method is effective and efficient, even for scaled and skewed road signs in complicated scenes. On the average, it takes 4-50 and 11 ms for detection and recognition, respectively. Thus, the proposed method is adapted to be implemented in real time.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages68-75
Number of pages8
DOIs
StatePublished - 1 Dec 2005
Event7th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2005 - Antwerp, Belgium
Duration: 20 Sep 200523 Sep 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3708 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2005
CountryBelgium
CityAntwerp
Period20/09/0523/09/05

Fingerprint Dive into the research topics of 'A fast method to detect and recognize scaled and skewed road signs'. Together they form a unique fingerprint.

Cite this