Road sign detection and recognition from video stream using HSV, contourlet transform and local energy based shape histogram

Usman Zakir; Eran A. Edirishinghe; Amir Hussain

doi:10.1007/978-3-642-31561-9_46

Road sign detection and recognition from video stream using HSV, contourlet transform and local energy based shape histogram

Usman Zakir^*
, Eran A. Edirishinghe
, Amir Hussain

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

This paper describes an efficient approach towards road sign detection and recognition. The proposed system is divided into three sections namely; Colour Segmentation of the road traffic signs using the HSV colour space considering varying lighting conditions, Shape Classification using the Contourlet Transform considering occlusion and rotation of the candidate signs and the Recognition of the road traffic signs using features of a Local Energy based Shape Histogram (LESH). We have provided three experimental results and a detailed analysis to justify that the algorithm described in this paper is robust enough to detect and recognize road signs under varying weather, occlusion, rotation and scaling conditions using video stream.

Original language	English
Title of host publication	Advances in Brain Inspired Cognitive Systems - 5th International Conference, BICS 2012, Proceedings
Pages	411-419
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-642-31561-9_46
State	Published - 2012
Externally published	Yes
Event	5th International Conference on Advances in Brain Inspired Cognitive Systems, BICS 2012 - Shenyang, China Duration: 11 Jul 2012 → 14 Jul 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7366 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	5th International Conference on Advances in Brain Inspired Cognitive Systems, BICS 2012
Country/Territory	China
City	Shenyang
Period	11/07/12 → 14/07/12

Keywords

And Autonomous Vehicles
Contourlet Transform
HSV
LESH
Road Signs

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-31561-9_46

Cite this

Zakir, U., Edirishinghe, E. A., & Hussain, A. (2012). Road sign detection and recognition from video stream using HSV, contourlet transform and local energy based shape histogram. In Advances in Brain Inspired Cognitive Systems - 5th International Conference, BICS 2012, Proceedings (pp. 411-419). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7366 LNAI). https://doi.org/10.1007/978-3-642-31561-9_46

Zakir, Usman ; Edirishinghe, Eran A. ; Hussain, Amir. / Road sign detection and recognition from video stream using HSV, contourlet transform and local energy based shape histogram. Advances in Brain Inspired Cognitive Systems - 5th International Conference, BICS 2012, Proceedings. 2012. pp. 411-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{b2892d6fcc3649a1a5371ffb6d5abed6,

title = "Road sign detection and recognition from video stream using HSV, contourlet transform and local energy based shape histogram",

abstract = "This paper describes an efficient approach towards road sign detection and recognition. The proposed system is divided into three sections namely; Colour Segmentation of the road traffic signs using the HSV colour space considering varying lighting conditions, Shape Classification using the Contourlet Transform considering occlusion and rotation of the candidate signs and the Recognition of the road traffic signs using features of a Local Energy based Shape Histogram (LESH). We have provided three experimental results and a detailed analysis to justify that the algorithm described in this paper is robust enough to detect and recognize road signs under varying weather, occlusion, rotation and scaling conditions using video stream.",

keywords = "And Autonomous Vehicles, Contourlet Transform, HSV, LESH, Road Signs",

author = "Usman Zakir and Edirishinghe, \{Eran A.\} and Amir Hussain",

year = "2012",

doi = "10.1007/978-3-642-31561-9\_46",

language = "English",

isbn = "9783642315602",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "411--419",

booktitle = "Advances in Brain Inspired Cognitive Systems - 5th International Conference, BICS 2012, Proceedings",

note = "5th International Conference on Advances in Brain Inspired Cognitive Systems, BICS 2012 ; Conference date: 11-07-2012 Through 14-07-2012",

}

Zakir, U, Edirishinghe, EA & Hussain, A 2012, Road sign detection and recognition from video stream using HSV, contourlet transform and local energy based shape histogram. in Advances in Brain Inspired Cognitive Systems - 5th International Conference, BICS 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7366 LNAI, pp. 411-419, 5th International Conference on Advances in Brain Inspired Cognitive Systems, BICS 2012, Shenyang, China, 11/07/12. https://doi.org/10.1007/978-3-642-31561-9_46

Road sign detection and recognition from video stream using HSV, contourlet transform and local energy based shape histogram. / Zakir, Usman; Edirishinghe, Eran A.; Hussain, Amir.
Advances in Brain Inspired Cognitive Systems - 5th International Conference, BICS 2012, Proceedings. 2012. p. 411-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7366 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Road sign detection and recognition from video stream using HSV, contourlet transform and local energy based shape histogram

AU - Zakir, Usman

AU - Edirishinghe, Eran A.

AU - Hussain, Amir

PY - 2012

Y1 - 2012

N2 - This paper describes an efficient approach towards road sign detection and recognition. The proposed system is divided into three sections namely; Colour Segmentation of the road traffic signs using the HSV colour space considering varying lighting conditions, Shape Classification using the Contourlet Transform considering occlusion and rotation of the candidate signs and the Recognition of the road traffic signs using features of a Local Energy based Shape Histogram (LESH). We have provided three experimental results and a detailed analysis to justify that the algorithm described in this paper is robust enough to detect and recognize road signs under varying weather, occlusion, rotation and scaling conditions using video stream.

AB - This paper describes an efficient approach towards road sign detection and recognition. The proposed system is divided into three sections namely; Colour Segmentation of the road traffic signs using the HSV colour space considering varying lighting conditions, Shape Classification using the Contourlet Transform considering occlusion and rotation of the candidate signs and the Recognition of the road traffic signs using features of a Local Energy based Shape Histogram (LESH). We have provided three experimental results and a detailed analysis to justify that the algorithm described in this paper is robust enough to detect and recognize road signs under varying weather, occlusion, rotation and scaling conditions using video stream.

KW - And Autonomous Vehicles

KW - Contourlet Transform

KW - HSV

KW - LESH

KW - Road Signs

UR - https://www.scopus.com/pages/publications/84865240657

U2 - 10.1007/978-3-642-31561-9_46

DO - 10.1007/978-3-642-31561-9_46

M3 - Conference contribution

AN - SCOPUS:84865240657

SN - 9783642315602

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 411

EP - 419

BT - Advances in Brain Inspired Cognitive Systems - 5th International Conference, BICS 2012, Proceedings

T2 - 5th International Conference on Advances in Brain Inspired Cognitive Systems, BICS 2012

Y2 - 11 July 2012 through 14 July 2012

ER -

Zakir U, Edirishinghe EA, Hussain A. Road sign detection and recognition from video stream using HSV, contourlet transform and local energy based shape histogram. In Advances in Brain Inspired Cognitive Systems - 5th International Conference, BICS 2012, Proceedings. 2012. p. 411-419. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-31561-9_46

Road sign detection and recognition from video stream using HSV, contourlet transform and local energy based shape histogram

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this