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Understanding interface recoloring aspects by colorblind people: a user study

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Abstract

The current web technologies make intensive the use of colors in web pages. Nowadays, colors are essential in the design of interfaces and play a central role in the distinction and comprehension of information. However, this affects colorblind users, i.e., those who have difficulties in recognizing or distinguishing colors. This paper presents a user study involving colorblind people to empirically investigate several aspects related to the recoloring of web interfaces. We aim to detect limitations, barriers, and needs about these users’ interaction with web pages. Our employed evaluation investigates indicators of satisfaction (contentment) and pleasantness (enjoyable) for several scenarios of interface recoloring adaptation. We found a ranking of application for interface adaptation techniques with the use of recoloring algorithms. The obtained results reveal the advantages of considering the colorblind individual’s needs and preferences for the development of adaptive systems. Our contribution can enhance web interface accessibility based on user interface adaptation techniques.

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Notes

  1. https://www.facebook.com/groups/592110540817526/?fref=ts.

  2. https://www.facebook.com/groups/daltonismo/?fref=ts.

  3. https://www.facebook.com/acessibilidadedaltonicos/?fref=ts.

  4. https://www.facebook.com/Tenho-marido-dalt%C3%B4nico-460913317343695/?fref=ts.

  5. https://www.limesurvey.org/.

  6. The web interface cases were converted in images files before applying the algorithms.

  7. https://www.w3.org/TR/UNDERSTANDING-WCAG20/visual-audio-contrast-contrast.html.

  8. http://colororacle.org/.

  9. http://www.color-blindness.com/coblis-color-blindness-simulator.

  10. Although we performed the analysis separately, it did not present statistical relevance differences, so we decided to present the results all together.

  11. All presented statements are translations made by the authors from Portuguese original comments.

  12. The opinions, hypotheses and conclusions or recommendations expressed in this material are the responsibility of the authors and do not necessarily reflect the views of FAPESP.

References

  1. Bailey, J.D.: Color Vision Deficiency: A Concise Tutorial for Optometry and Ophthalmology, p. 16. Richmond Products Inc, Albuquerque (2010)

    Google Scholar 

  2. Flatla, D.: SPRWeb: preserving subjective responses to website colour schemes through automatic recolouring. In: The Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, NY, USA, pp. 2069–2078 (2013)

  3. Flatla, D.R.: Accessibility for individuals with color vision deficiency. In: The Proceedings of the 24th Annual ACM Symposium Adjunct on User Interface Software and Technology (UIST ‘11 Adjunct). ACM, New York, NY, USA, pp. 31–34 (2012)

  4. Huang, J., Wu, S., Chen, C.: Enhancing color representation for the color vision impaired. In: The Proceedings of the ECCV Workshop on Computer Vision Applications for the Visually Impaired, Villeurbanne, France, pp. 12 (2008)

  5. Troiano, L., Birtolo, C., Miranda, M.: Adapting palettes to color vision deficiencies by genetic algorithm. In: The Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation—GECCO’08. New York, New York, USA, pp. 1065–1072 (2008)

  6. Kuhn, G.R., Oliveira, M.M., Fernandes, L.A.F.: An efficient naturalness-preserving image-recoloring method for dichromats. In: IEEE Transactions on Visualization and Computer Graphics, Los Alamitos, CA, USA, vol. 14, pp. 1747–1754 (2008)

  7. Ling, J., Schaik, P.V.: The influence of font type and line length on visual search and information retrieval in web pages. Int. J. Hum. Comput. Stud. 64, 395–404 (2006)

    Article  Google Scholar 

  8. Rasche, K., Geist, R., Westall, J.: Re-coloring images for gamuts of lower dimension. In: Computer Graphics Forum, Clemson, SC, USA, pp. 423–432 (2005)

  9. W3C Brasil: (2014). World Wide Web Consortium. http://www.w3.org/Translations/WCAG20-pt-PT. Accessed 12 July 2015

  10. Mereuta, A., Aupetit, S., Monmarché, N., Slimane, M.: Web page textual color contrast compensation for CVD users using optimization methods. J. Math. Model. Algorithms Oper. Res. 13, 447–470 (2013)

    Article  Google Scholar 

  11. Wakita, K., Shimamura, K.: (2005). SmartColor: disambiguation framework for the colorblind. In: The Proceedings of the SIG ACCESS Conference on Assistive Technologies, New York, NY, USA, pp. 158–165

  12. Iaccarino, G., Malandrino, D., Percio, M., Scarano, V.: (2006). Efficient edge-services for colorblind users. In: The Proceedings of the 15th International Conference on World Wide Web—WWW’06. New York, New York, USA, pp. 919–920

  13. Malandrino, D., Mazzoni, F., Riboni, D., Bettini, C., Colajanni, M., Scarano, V.: MIMOSA: context-aware adaptation for ubiquitous web access. Personal Ubiquitous Comput. 14(4), 301–320 (2009)

    Article  Google Scholar 

  14. Jefferson, L., Harvey, R.: Accommodating color blind computer users. In: The Proceedings of the 8th International ACM SIGACCESS Conference on Computers and Accessibility—Assets’06. New York, New York, USA. pp. 40–47 (2006)

  15. Iaccarino, G., Malandrino, D., Scarano, V.: Personalizable edge services for Web accessibility. In: The Proceedings of the International Cross-Disciplinary Workshop on Web Accessibility (W4A): Building the Mobile Web: Rediscovering Accessibility? New York, NY, USA, pp. 23–32 (2006)

  16. Ishihara, S.: Test for Colour-Blindness. 24 Plates Edition, p. 33. Tokyo/Kyoto, Japan (1972)

  17. Flatla, D.R., Gutwin, C.: Individual models of color differentiation to improve interpretability of information visualization. In: The Proceedings of the 28th International Conference on Human Factors in Computing Systems—CHI’10. Atlanta, Georgia, USA, pp. 2563 (2010)

  18. Flatla, D.R., Gutwin, C.: Improving calibration time and accuracy for situation-specific models of color differentiation. In: The Proceedings of the 13th International ACM SIGACCESS Conference on Computers and Accessibility—ASSETS, Dundee, Scotland, UK. pp. 195–202 (2011)

  19. Flatla, D.R., Gutwin, C.: So that’s what you see! Building understanding with personalized simulations of colour vision deficiency. In: The Proceedings of the 14th International ACM SIGACCESS Conference on Computers and accessibility, Boulder, Colorado, USA, pp. 167–174 (2012)

  20. Flatla, D., Gutwin, C.: SSMRecolor: improving recoloring tools with situation-specific models of color differentiation. In: The Proceedings of the SIGCHI Conference on Human Factors in Computing System. Austin, Texas, USA, pp. 2297–2306 (2012)

  21. Kuhn, G.R.: Image recoloring for color-vision deficients. Master Dissertation in Computer Science. Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil, pp. 74 (2009)

  22. Huang, J.B., Chen, C.S., Jen, T.C., Wang, S.J.: Image recolorization for the colorblind. In: The Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. Taipei, Taiwan, pp. 1161–1164 (2009)

  23. Machado, G.M., Oliveira, M.M.: Real-time temporal-coherent color contrast enhancement for dichromats. In: Computer Graphics Forum, pp. 933–942. Blackwell, Oxford (2010)

    Google Scholar 

  24. Tanuwidjaja, E., Huynh, D., Koa, K., Nguyen, C., Shao, C., Torbett, P., Emmenegger, C., Weibel, N.: Chroma: a wearable augmented-reality solution for color blindness. In: UBICOMP 2014, New York, NY, USA, pp. 799–810 (2014)

  25. Simon-Liedtke, J., Flatla, D.R., Bakken, E.N.:. Checklist for Daltonization methods: requirements and characteristics of a good recolouring method. Electron. Imaging 18, 21–27 (2017)

    Article  Google Scholar 

  26. Tigwell, G.W., Flatla, D.R., Archibald, N.D.: ACE: a colour palette design tool for balancing aesthetics and accessibility. ACM Trans Access. Comput. 9(2), 32 (2017)

    Article  Google Scholar 

  27. Wilcoxon, F.: Individual comparisons by ranking methods. Biom. Bull. 1, 80–83 (1945)

    Article  Google Scholar 

  28. Ritchie, J., Spencer, L.: Qualitative data analysis for applied policy research. In: Bryman, A., Burgess, R.G. (eds.) Analysing Qualitative Data, pp. 173–194. Routledge, London (1994)

    Chapter  Google Scholar 

  29. Gale, N.K., Heath, G., Cameron, E., Rashid, S., Redwood, S.: Using the framework method for the analysis of qualitative data in multi-disciplinary health research. BMC Med. Res. Methodol. 13(1), 8 (2013)

    Article  Google Scholar 

  30. Higuchi, K.: Kh coder. http://khc.sourceforge.net/en/. Accessed June 2018

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Acknowledgements

We would like to thank the São Paulo Research Foundation (FAPESP) (Grant #2017/02325-5)Footnote 12.

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Correspondence to Julio Cesar Dos Reis.

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de Araújo, R.J., Dos Reis, J.C. & Bonacin, R. Understanding interface recoloring aspects by colorblind people: a user study. Univ Access Inf Soc 19, 81–98 (2020). https://doi.org/10.1007/s10209-018-0631-7

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