A new approach to image enhancement for the visually impaired

Conference paper

Gao, X. and Loomes, M. 2016. A new approach to image enhancement for the visually impaired. IS&T International Symposium on Electronic Imaging 2016 - Color Imaging XXI: Displaying, Processing, Hardcopy, and Applications. San Francisco, CA, USA 14 - 18 Feb 2016 Society for Imaging Science and Technology. pp. 1-7 https://doi.org/10.2352/ISSN.2470-1173.2016.20.COLOR-325
TypeConference paper
TitleA new approach to image enhancement for the visually impaired
AuthorsGao, X. and Loomes, M.
Abstract

This works aims at enhancing images by using the colour appearance model CIECAM02 for the visually impaired to view digital displays to complement the existing image processing approaches with a reference to normal visions. Specifically, by studying the images perceived by low-vision users, the colour ranges of these perceived views are compared with those viewed by normal vision and then characterized and represented using CIECAM02 correlates, which include lightness, colourfulness, and hue. For low-vision users, the extents of these attributes are therefore obtained. Subsequently, for any input image, these CIECAM02 attributes are subsequently enhanced through histogram equalizer technique within their respective ranges for low-vision users. In comparison with the approach of RGB histogram equalizer, the preliminary result has shown that the proposed method appears to be better to enhance the contents depicted in an image. The evaluation experiment was carried out using an array of low-vision simulator glasses to be worn by a group of subjects with normal vision. The next stage of the work remains to invite real low-vision users to evaluate the proposed work.
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ConferenceIS&T International Symposium on Electronic Imaging 2016 - Color Imaging XXI: Displaying, Processing, Hardcopy, and Applications
Page range1-7
Proceedings TitleProceedings of the IS&T International Symposium on Electronic Imaging: Color Imaging XXI: Displaying, Processing, Hardcopy, and Applications
SeriesElectronic Imaging
ISSN2470-1173
PublisherSociety for Imaging Science and Technology
Publication dates
Print14 Feb 2016
Publication process dates
Deposited25 Feb 2016
Accepted01 Nov 2015
Output statusPublished
Publisher's version
Copyright Statement

Xiaohong W. Gao and Monica Loomes, “A new approach to image enhancement for the visually impaired,” IS&T Electronic Imaging, Color Imaging XXI: Displaying, Processing, Hardcopy, and Applications, pg. COLOR-325.1 (2016).
©2016 Society for Imaging Science and Technology. Reprinted with permission of IS&T: The Society for Imaging Science and Technology sole copyright owners of Electronic Imaging, Color Imaging XXI: Displaying, Processing, Hardcopy, and Applications.

Additional information

Gao, X., & Loomes, M. (2016). A new approach to image enhancement for the visually impaired. Electronic Imaging, 2016(20), 1–7. doi:10.2352/issn.2470-1173.2016.20.color-325

Digital Object Identifier (DOI)https://doi.org/10.2352/ISSN.2470-1173.2016.20.COLOR-325
Scopus EID2-s2.0-85086689397
LanguageEnglish
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Colour vision model-based approach for segmentation of traffic signs
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
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
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