Improved efficiency of road sign detection and recognition by employing Kalman filter: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings

Usman Zakir, Amir Hussain, Liaqat Ali, Bin Luo

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

1 Citation (Scopus)

Abstract

This paper describes an efficient approach towards road sign detection, and recognition. The proposed system is divided into three sections namely: Road Sign Detection where Colour Segmentation of the road traffic signs is carried out using HSV colour space considering varying lighting conditions and Shape Classification is achieved by using Contourlet Transform, considering possible occlusion and rotation of the candidate signs. Road Sign Tracking is introduced by using Kalman Filter where object of interest is tracked until it appears in the scene. Finally, Road Sign Recognition is carried out on successfully detected and tracked road sign by using features of a Local Energy based Shape Histogram (LESH). Experiments are carried out on 15 distinctive classes of road signs to justify that the algorithm described in this paper is robust enough to detect, track and recognize road signs under varying weather, occlusion, rotation and scaling conditions using video stream.
LanguageEnglish
Title of host publicationAdvances in Brain Inspired Cognitive Systems
EditorsDerong Liu, Cesare Alippi, Dongbin Zhao, Amir Hussain
Place of PublicationBerlin
Pages216-224
Number of pages9
DOIs
Publication statusPublished - 11 Jun 2013
Event6th International Conference, BICS 2013 - Beijing, China
Duration: 9 Jun 201311 Jun 2013

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Volume7888
ISSN (Print)0302-9743

Conference

Conference6th International Conference, BICS 2013
CountryChina
CityBeijing
Period9/06/1311/06/13

Fingerprint

Kalman filters
Traffic signs
Color
Lighting
Mathematical transformations
Experiments

Keywords

  • SVM
  • road signs
  • HSV
  • contourlet transform
  • LESH
  • colour segmentation
  • autonomous vehicles
  • kalman filter

Cite this

Zakir, U., Hussain, A., Ali, L., & Luo, B. (2013). Improved efficiency of road sign detection and recognition by employing Kalman filter: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings. In D. Liu, C. Alippi, D. Zhao, & A. Hussain (Eds.), Advances in Brain Inspired Cognitive Systems (pp. 216-224). (Lecture Notes in Computer Science; Vol. 7888). Berlin. https://doi.org/10.1007/978-3-642-38786-9_25
Zakir, Usman ; Hussain, Amir ; Ali, Liaqat ; Luo, Bin. / Improved efficiency of road sign detection and recognition by employing Kalman filter : 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings. Advances in Brain Inspired Cognitive Systems. editor / Derong Liu ; Cesare Alippi ; Dongbin Zhao ; Amir Hussain. Berlin, 2013. pp. 216-224 (Lecture Notes in Computer Science).
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abstract = "This paper describes an efficient approach towards road sign detection, and recognition. The proposed system is divided into three sections namely: Road Sign Detection where Colour Segmentation of the road traffic signs is carried out using HSV colour space considering varying lighting conditions and Shape Classification is achieved by using Contourlet Transform, considering possible occlusion and rotation of the candidate signs. Road Sign Tracking is introduced by using Kalman Filter where object of interest is tracked until it appears in the scene. Finally, Road Sign Recognition is carried out on successfully detected and tracked road sign by using features of a Local Energy based Shape Histogram (LESH). Experiments are carried out on 15 distinctive classes of road signs to justify that the algorithm described in this paper is robust enough to detect, track and recognize road signs under varying weather, occlusion, rotation and scaling conditions using video stream.",
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Zakir, U, Hussain, A, Ali, L & Luo, B 2013, Improved efficiency of road sign detection and recognition by employing Kalman filter: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings. in D Liu, C Alippi, D Zhao & A Hussain (eds), Advances in Brain Inspired Cognitive Systems. Lecture Notes in Computer Science, vol. 7888, Berlin, pp. 216-224, 6th International Conference, BICS 2013, Beijing, China, 9/06/13. https://doi.org/10.1007/978-3-642-38786-9_25

Improved efficiency of road sign detection and recognition by employing Kalman filter : 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings. / Zakir, Usman; Hussain, Amir; Ali, Liaqat; Luo, Bin.

Advances in Brain Inspired Cognitive Systems. ed. / Derong Liu; Cesare Alippi; Dongbin Zhao; Amir Hussain. Berlin, 2013. p. 216-224 (Lecture Notes in Computer Science; Vol. 7888).

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Zakir U, Hussain A, Ali L, Luo B. Improved efficiency of road sign detection and recognition by employing Kalman filter: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings. In Liu D, Alippi C, Zhao D, Hussain A, editors, Advances in Brain Inspired Cognitive Systems. Berlin. 2013. p. 216-224. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-642-38786-9_25