Colour vision model-based approach for segmentation of traffic signs

Article


Gao, X., Hong, K., Passmore, P., Podladchikova, L. and Shaposhnikov, D. 2008. Colour vision model-based approach for segmentation of traffic signs. EURASIP Journal on Image and Video Processing. 2008. https://doi.org/10.1155/2008/386705
TypeArticle
TitleColour vision model-based approach for segmentation of traffic signs
AuthorsGao, X., Hong, K., Passmore, P., Podladchikova, L. and Shaposhnikov, D.
Abstract

This paper presents a new approach to segment traffic signs from the rest of a scene via CIECAM, a colour appearance model. This approach not only takes CIECAM into practical application for the first time since it was standardised in 1998, but also introduces a new way of segmenting traffic signs in order to improve the accuracy of colour-based approach. Comparison with the other CIE spaces, including CIELUV and CIELAB, and RGB colour space is also carried out. The results show that CIECAM performs better than the other three spaces with 94%, 90%, and 85% accurate rates for sunny, cloudy, and rainy days, respectively. The results also confirm that CIECAM does predict the colour appearance similar to average observers.

Research GroupArtificial Intelligence group
PublisherHindawi
JournalEURASIP Journal on Image and Video Processing
ISSN
Electronic1687-5176
Publication dates
Print2008
Publication process dates
Deposited21 Feb 2012
Output statusPublished
Publisher's version
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Copyright Statement

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Digital Object Identifier (DOI)https://doi.org/10.1155/2008/386705
Scopus EID2-s2.0-41249085710
Web of Science identifierWOS:000207762400001
LanguageEnglish
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The anatomy of teleneurosurgery in China
Gao, X. 2011. The anatomy of teleneurosurgery in China. International Journal of Telemedicine and Applications. 2011. https://doi.org/10.1155/2011/353405
Integration of geographic information system and RADARSAT synthetic aperture radar data using a self-organizing map network as compensation for realtime ground data in automatic image classification
Shepherd, I., Passmore, P. and Kamal, M. 2010. Integration of geographic information system and RADARSAT synthetic aperture radar data using a self-organizing map network as compensation for realtime ground data in automatic image classification. Journal of Applied Remote Sensing. 4 (1), pp. 1-13. https://doi.org/10.1117/1.3457166
Statistical analysis for brain EIT images using SPM.
Zhang, Y., Passmore, P., Yerworth, R. and Bayford, R. 2005. Statistical analysis for brain EIT images using SPM. Institute of Electrical and Electronics Engineers. pp. 60-67 https://doi.org/10.1109/MEDIVIS.2005.17
Models of cell assembly decay
Passmore, P. and Huyck, C. 2008. Models of cell assembly decay. Institute of Electrical and Electronics Engineers. pp. 1-6 https://doi.org/10.1109/UKRICIS.2008.4798946
Visualization of multidimensional and multimodal tomographic medical imaging data, a case study
Zhang, Y., Passmore, P. and Bayford, R. 2009. Visualization of multidimensional and multimodal tomographic medical imaging data, a case study. Philosophical Transactions of the Royal Society of London. A: Mathematical and Physical Sciences. 367 (1900), pp. 3121-3148. https://doi.org/10.1098/rsta.2009.0084
Texture-based 3d image retrieval for medical applications
Gao, X., Qian, Y., Hui, R., Loomes, M., Comley, R., Barn, B., Chapman, A. and Rix, J. 2010. Texture-based 3d image retrieval for medical applications. Macedo, M. (ed.) IADIS International Conference e-Health 2010. Freiburg, Germany 29 - 31 Jul 2010 IADIS. pp. 101-108
Application of mesh morphing techniques in modelling 3D objects
Gao, X. and Hassan, M. 2010. Application of mesh morphing techniques in modelling 3D objects. Annual International Conference on Computer Games Multimedia and Allied Technology. Singapore 06 - 07 Apr 2010 Global Science and Technology Forum. https://doi.org/10.5176/978-981-08-5480-5_048
Invariance of visual perception
Chikhman, V., Shelepin, Y., Foreman, N., Passmore, P., Vakhrameeva, O. and Pronin, S. 2008. Invariance of visual perception. Experimental Psychology. 1, pp. 7-33.
Viewpoint invariance in the recognition of 3-D depth-rotated figures
Chikhman, V., Shelepin, Y., Foreman, N. and Passmore, P. 2008. Viewpoint invariance in the recognition of 3-D depth-rotated figures. Perception. 37.
The estimation of quantitative ranges of invariance in visual perception
Chikhman, V., Shelepin, Y., Vakhrameeva, O., Pronin, S., Foreman, N. and Passmore, P. 2009. The estimation of quantitative ranges of invariance in visual perception. Perception. 38.
Road sign recognition by one fixation of space-variant sensor.
Gao, X., Shaposhnikov, D., Podladchikova, L., Golovan, A., Shevtsova, N. and Hong, K. 2002. Road sign recognition by one fixation of space-variant sensor. in: Gorodnich, D. and Zhang, H. (ed.) Vision Interface ’2002: proceedings Quebec Canadian Image Processing and Pattern Recognition Society.
Invariant recognition of traffic signs
Gao, X., Shaposhnikov, D., Podladchikova, L., Shevtsova, N. and Golovan, A. 2002. Invariant recognition of traffic signs.
Application of the behavioural model of vision for invariant recognition of facial and traffic sign images.
Gao, X., Shaposhnikov, D., Podladchikova, L., Golovan, A., Shevtsova, N., Gusakova, V. and Gizatdinova, Y. 2003. Application of the behavioural model of vision for invariant recognition of facial and traffic sign images. in: Gulaev, Y. and Galushkin, A. (ed.) Neurocomputers and their application. [In Russian] Moscow Radiotechnics.
Image classification based on the informative regions properties.
Gao, X., Podladchikova, L. and Shaposhnikov, D. 2003. Image classification based on the informative regions properties. in: Proceedings of PRIA-6-2002 : 6th International conference on pattern recognition and image analysis: new information technologies. MAIK Nauka/Interperiodica. pp. 439-441
Image retrieval through perceptual shape modelling.
Gao, X., Ren, M., Riley, K., Eakins, J. and Briggs, P. 2001. Image retrieval through perceptual shape modelling. London Council for Museums, Archives and Libraries.
Telemedicine in Europe.
Gao, X. 2006. Telemedicine in Europe. ChinaPacs. Beijing 14 - 16 Apr 2006
A new approach to traffic sign recognition
Gao, X., Podladchikova, L., Shaposhnikov, D., Hong, K., Batty, S., Golovan, A., Gusakova, V. and Shevtsova, N. 2002. A new approach to traffic sign recognition. in: Arabnia, H. and Mun, Y. (ed.) Proceedings of the international conference on imaging science, systems, and technology: CISST'02. Athens CSREA Press.
Road sign recognition by means of the behavioural model of vision.
Gao, X., Golovan, A., Hong, K., Podladchikova, L. and Shevtsova, N. 2002. Road sign recognition by means of the behavioural model of vision. in: Proceedings of the third all-Russian conference on neuroinformatics [In Russian]. Moscow. pp. 63-69
Colour reproduction for tele-imaging systems
Gao, X. and He, P. 2006. Colour reproduction for tele-imaging systems. Computerized medical imaging and graphics. 30 (6-7), pp. 79-84.
Measurement of vessel diameters on retinal for cardiovascular studies.
Gao, X., Bharath, A., Stanton, A., Hughes, A., Chapman, N. and Thom, S. 2001. Measurement of vessel diameters on retinal for cardiovascular studies. in: Claridge, E., Bamber, J. and Marlow, K. (ed.) Medical image understanding and analysis 2001. Medical Imaging Understanding and Analysis.
Extraction of sagittal symmetry planes from PET images.
Gao, X., Batty, S., Clark, J., Fryer, T., Blandford, A. and International Association of Science and Technology for Development. 2001. Extraction of sagittal symmetry planes from PET images. in: Hamza, M. (ed.) Visualization, imaging and image processing: proceedings of the IASTED international conference. Calgary IASTED. pp. 428-433
The state of art of medical displays.
Gao, X. 2006. The state of art of medical displays. EuroPacs 2006. Trondheim, Norway 14 - 17 Jun 2006
Towards archiving wallpaper images
Gao, X., Qian, Y., Tully, T. and Hendon, Z. 2004. Towards archiving wallpaper images. in: Hamza, M. (ed.) Proceedings of the seventh IASTED international conference on computer graphics and imaging. Anaheim Acta Press. pp. 305-309
High-precision detection of facial landmarks to estimate head motions based on vision models
Gao, X., Anishenko, S., Shaposhnikov, D., Podladchikova, L., Batty, S. and Clark, J. 2007. High-precision detection of facial landmarks to estimate head motions based on vision models. Journal of computer sciences. 3 (7), pp. 528-532.
Content-based retrieval of PET images via localised anatomical texture measurements and mean activity levels
Gao, X., Batty, S., Clark, J. and Fryer, T. 2006. Content-based retrieval of PET images via localised anatomical texture measurements and mean activity levels. Computerized medical imaging and graphics. 30 (6-7), pp. 70-74.
Extraction of physiological information from 3D PET brain images.
Gao, X., Batty, S., Fryer, T., Clark, J., Turkheimer, F. and International Association of Science and Technology for Development. 2003. Extraction of physiological information from 3D PET brain images. in: Villanueva, J. (ed.) Visualization imaging and image processing. Acta Press. pp. 401-405
Extraction of features from 3D PET images.
Gao, X., Batty, S., Clark, J. and Fryer, T. 2002. Extraction of features from 3D PET images. in: Houston, A. and Zwiggelar, R. (ed.) Medical image understanding and analysis 2002. BMVA.
Towards archiving 3D PET brain images based on their physiological and visual content.
Gao, X., Batty, S., Clark, J., Fryer, T. and Turkheimer, F. 2002. Towards archiving 3D PET brain images based on their physiological and visual content. International conference on diagnostic imaging and analysis. Shanghai, China 18 - 20 Aug 2002
A new approach to estimation of non-isotropic scale factors for correction of MR distortion
Gao, X., Hui, R., White, A.S. and Tian, Z. 2009. A new approach to estimation of non-isotropic scale factors for correction of MR distortion. International Journal of Computer Assisted Radiology and Surgery. 4 (s1), pp. s349-s350.
Task based visualization of 5D brain EIT data
Zhang, Y., Passmore, P. and Bayford, R. 2009. Task based visualization of 5D brain EIT data. SAC09: The 2009 ACM Symposium on Applied Computing. Honolulu Hawaii, USA 08 - 12 Mar 2009 New York Association for Computing Machinery (ACM). pp. 831-835 https://doi.org/10.1145/1529282.1529459
Dynamics in proportionate selection.
Mitchell, I., Agrawal, A., Litovski, I. and Passmore, P. 2005. Dynamics in proportionate selection. in: International Conference on Adaptive and Natural Computnig Alogorithms, Coimbra, Portugal. Proceedings. Vienna. Springer. pp. 226-229
Classification of images on the basis of the properties of informative regions.
Gao, X., Shaposhnikov, D. and Podladchikova, L. 2003. Classification of images on the basis of the properties of informative regions. Pattern Recognition and Image Analysis. 13 (2), pp. 349-352.
A fast approach to segmentation of PET brain images for extraction of features
Gao, X. and Clark, J. 2008. A fast approach to segmentation of PET brain images for extraction of features. Gao, X., Loomes, M., Comley, R., Muller, H. and Luo, S. (ed.) International Conference on Medical Imaging and Informatics (MIMI 2007). Beijing, China 14 - 16 Aug 2007 Berlin, Heidelberg Springer. https://doi.org/10.1007/978-3-540-79490-5_25
Prototype system for semantic retrieval of neurological PET images
Batty, S., Clark, J., Fryer, T. and Gao, X. 2008. Prototype system for semantic retrieval of neurological PET images. Gao, X., Muller, H., Loomes, M., Comley, R. and Luo, S. (ed.) International Conference on Medical Imaging and Informatics (MIMI 2007). Beijing, China 14 - 16 Aug 2007 Berlin, Heidelberg Springer. https://doi.org/10.1007/978-3-540-79490-5_23
Toward a robust system to monitor the head motions during PET based on facial landmarks detection: a new approach
Anishenko, S., Osimov, V., Shaposhnikov, D., Podladchikova, L., Comley, R. and Gao, X. 2008. Toward a robust system to monitor the head motions during PET based on facial landmarks detection: a new approach. Puuronen, S., Pechenizkiy, M., Tsymbal, A. and Lee, D. (ed.) 21st IEEE International Symposium on Computer-Based Medical Systems. Jyvaskyla, Finland 17 - 19 Jun 2008 IEEE Computer Society. pp. 50-52 https://doi.org/10.1109/CBMS.2008.19
Detection of head motions using a vision model
Gao, X., Shaposhnikov, D., Podladchikova, L., Batty, S. and Clark, J. 2007. Detection of head motions using a vision model. Bashshur, R. (ed.) 3rd IASTED International Conference on Telehealth. Montreal, QC, Canada 31 May - 01 Jun 2007 Anaheim, CA Acta Press. pp. 167-171
Recognition of traffic signs based on their colour and shape features extracted using human vision models
Gao, X., Podladchikova, L., Shaposhnikov, D., Hong, K. and Shevtsova, N. 2006. Recognition of traffic signs based on their colour and shape features extracted using human vision models. Journal of Visual Communication and Image Representation. 17 (4), pp. 675-685. https://doi.org/10.1016/j.jvcir.2005.10.003
Visualization and post-processing of 5D Brain Images
Zhang, Y., Passmore, P. and Bayford, R. 2005. Visualization and post-processing of 5D Brain Images. 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Shanghai, China 01 - 04 Sep 2005 IEEE. pp. 1083-1086 https://doi.org/10.1109/IEMBS.2005.1616607
Colour management in telemedicine
Gao, X. 2004. Colour management in telemedicine. Hamza, M. (ed.) 7th IASTED International Conference on Computer Graphics and Imaging. Kauai, Hawaii, United States 16 - 18 Aug 2004 Anaheim, CA Acta Press. pp. 361-364
Application of vision models to traffic sign recognition
Gao, X., Shaposhnikov, D. and Podladchikova, L. 2004. Application of vision models to traffic sign recognition. Kaynak, O., Alpaydin, E., Oja, E. and Xu, L. (ed.) Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003. Istanbul, Turkey 26 - 29 Sep 2003 Berlin, Heidelberg Springer. https://doi.org/10.1007/3-540-44989-2_131
Towards content-based retrieval for wallpaper images
Qian, Y., Tully, C., Hendon, Z. and Gao, X. 2003. Towards content-based retrieval for wallpaper images. 7th IASTED International Conference on Computer Graphics and Imaging. Kauai, Hawaii, United States 16 - 18 Aug 2004 pp. 305-309
Vision models based identification of traffic signs
Gao, X., Podladchikova, L., Shaposhnikov, D., Shevtsova, N., Hong, K., Batty, S., Golovan, A. and Gusakova, V. 2002. Vision models based identification of traffic signs. 1st European Conference on Colour Graphics, Imaging, and Vision. University of Poitiers, France 02 - 05 Apr 2002 Society for Imaging Science and Technology.
Content based retrieval of lesioned brain images
Batty, S., Blandford, A., Clark, J., Fryer, T. and Gao, X. 2002. Content based retrieval of lesioned brain images. Siegel, E. and Huang, H. (ed.) SPIE Medical Imaging 2002. San Diego, California, United States 23 - 28 Feb 2002 Bellingham Society of Photo-optical Instrumentation Engineers (SPIE). https://doi.org/10.1117/12.466997
A method of vessel tracking for vessel diameter measurement on retinal images
Gao, X., Bharath, A., Stanton, A., Hughes, A., Chapman, N. and Thom, S. 2001. A method of vessel tracking for vessel diameter measurement on retinal images. 2001 International Conference on Image Processing. Thessaloniki, Greece 07 - 10 Oct 2001 IEEE.
Computer algorithms for the automated measurement of retinal arteriolar diameters
Chapman, N., Witt, N., Gao, X., Bharath, A., Stanton, A., Thom, S. and Hughes, A. 2001. Computer algorithms for the automated measurement of retinal arteriolar diameters. British Journal of Ophthalmology. 85 (1), pp. 74-79. https://doi.org/10.1136/bjo.85.1.74
Quantification and characterization of arteries in retinal images
Gao, X., Bharath, A., Stanton, A., Hughes, A., Chapman, N. and Thom, S. 2000. Quantification and characterization of arteries in retinal images. Computer Methods and Programs in Biomedicine. 63 (2), pp. 133-146. https://doi.org/10.1016/S0169-2607(00)00082-1