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Improving webtoon accessibility for color vision deficiency in South Korea using deep learning

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Abstract

The webtoon industry is experiencing significant growth in terms of its user base and revenue, rapidly expanding from the local market to international ones. However, despite this growth, its accessibility has not improved significantly, with most efforts focusing on providing more webtoon content within the platform. Not much is known about who is excluded from the webtoon industry. To address this, this research particularly focuses on color vision deficiency (CVD) accessibility of webtoon content. Adapting the design science research framework, this research followed the four steps of design science research: problem identification and motivation, development and demonstration, evaluation, and communication. First, it organized the CVD issues in South Korea. Then, it proposed a technical solution using a deep learning model. Specifically, this research used a Pix2Pix generative adversarial network-based recoloring algorithm and provided the translated images. We evaluated the solution by using colorblind filtering and in-depth interviews with individuals with CVD. This research provides a well-rounded accessibility study on the webtoon domain by identifying issues, proposing a deep learning solution, and evaluating that algorithm with the people with CVD. A total of seven CVD issues in webtoon contents have been identified. Deep learning-based image translation model has been developed to improve the accessibility of CVD people to webtoon content. This study contributes to both CVD and media accessibility by structurally organizing the sequence of problem solving for accessibility issues in the webtoon domain.

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Source: Naver Webtoon

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Similar content being viewed by others

Data availability

We used the dataset and source code to build an image translation model from the work of Li et al. [54] It can be found at: https://github.com/doubletry/pix2pix

Notes

  1. We used the dataset and source code to build an image translation model from the work of Li et al. [54]. It can be found at: https://github.com/doubletry/pix2pix.

References

  1. Dinis, M.G., Eusébio, C., Breda, Z.: Assessing social media accessibility: the case of the Rock in Rio Lisboa music festival. Int J. Event Festiv. Manag. 11(1), 26–46 (2020). https://doi.org/10.1108/IJEFM-02-2019-0012

    Article  Google Scholar 

  2. Yi, Y.J.: Web accessibility of healthcare web sites of Korean government and public agencies: a user test for persons with visual impairment. Univers. Access Inf. Soc. 19(1), 41–56 (2020). https://doi.org/10.1007/s10209-018-0625-5

    Article  Google Scholar 

  3. Wakita, K., Shimamura, K.: SmartColor: Disambiguation framework for the colorblind. In: Proceedings of the 7th International ACM SIGACCESS Conference on Computers and Accessibility—Assets ’05, 158. https://doi.org/10.1145/1090785.1090815 (2005)

  4. Beyond Market Insights: Webtoons market size, share, analysis, growth & forecast report. Beyond Market Insights. https://beyondmarketinsights.com/report/webtoons-market/ (2022). Accessed Dec 2022

  5. Kim, S.-I., Lee, Y.-J.: International diversification strategy of webtoon platforms -Focusing on Naver and Kakao webtoon in Japan-. Cartoon Animation Stud. 66, 589–629 (2022). https://doi.org/10.7230/KOSCAS.2022.66.589

    Article  Google Scholar 

  6. Jeong, J.: Webtoons go viral? The globalization processes of Korean digital comics. Korea J 60(1), 71–99 (2020). https://doi.org/10.25024/KJ.2020.60.1.71

    Article  Google Scholar 

  7. Cho, H.: The platformization of culture: webtoon platforms and media ecology in Korea and beyond. J. Asian Stud. 80(1), 73–93 (2021). https://doi.org/10.1017/S0021911820002405

    Article  Google Scholar 

  8. Kim, J., Yu, J.: Platformizing webtoons: the impact on creative and digital labor in South Korea. Soc. Media Soc. 5(4), 205630511988017 (2019). https://doi.org/10.1177/2056305119880174

    Article  Google Scholar 

  9. Yecies, B., Yang, J.J., Lu, Y.: Korean webtoons and collective innovation: expanding Europe’s creative industries through competitive localization. Innovation 33(4), 459–473 (2020). https://doi.org/10.1080/13511610.2020.1828839

    Article  Google Scholar 

  10. Webaim: Introduction to web accessibility. Institute for Disability Research, Policy, and https://webaim.org/intro/#people. Accessed 14 April 2020

  11. NULI: Classification of accessibility environment. NTS Corp. https://nuli.navercorp.com/community/article/42604 (2011). Accessed 28 March 2011

  12. Jordan, P., Oppegaard, B.: Media accessibility policy in theory and reality: Empirical outreach to audio description users in the United States. Ar**v:1809.05585 [Cs]. http://arxiv.org/abs/1809.05585 (2018)

  13. Okyayuz, A.Ş, Kaya, M.: Disability and the implication of coaccessibility: a case study on accessibility to the media in Turkey. Media Cult. Soc. 42(6), 987–1002 (2020). https://doi.org/10.1177/0163443720908133

    Article  Google Scholar 

  14. Peffers, K., Tuunanen, T., Rothenberger, M.A., Chatterjee, S.: A design science research methodology for information systems research. J. Manag. Inf. Syst. 24(3), 45–77 (2007). https://doi.org/10.2753/MIS0742-1222240302

    Article  Google Scholar 

  15. Iqbal, M.W., Shahzad, S.K., Ahmad, N., Amelio, A., Brodic, D.: Adaptive interface for color-blind people in mobile-phones. Int. Conf. Adv. Comput. Sci. (ICACS) 2018, 1–8 (2018). https://doi.org/10.1109/ICACS.2018.8333488

    Article  Google Scholar 

  16. Reinaldo, I., Pulungan, N.S., Darmadi, H.: Prototy** “Color in Life” edugame for dichromatic color blind awareness. Procedia Comput. Sci. 179, 773–780 (2021). https://doi.org/10.1016/j.procs.2021.01.070

    Article  Google Scholar 

  17. Espinda, S.D.: Color vision deficiency. A learning disability? J. Learn. Disabil. 6(3), 4 (1973)

    Article  Google Scholar 

  18. Uehara, A.: Colorable band: A wearable device to encourage daily decision making based on behavior of users with color vision deficiency. In: The 23rd International ACM SIGACCESS Conference on Computers and Accessibility, pp. 1–4. https://doi.org/10.1145/3441852.3476570 (2021)

  19. Kim, H., Ng, J.S.: Prevalence of color vision deficiency in an adult population in South Korea. Optom. Vis. Sci. 96(11), 866–873 (2019). https://doi.org/10.1097/OPX.0000000000001441

    Article  Google Scholar 

  20. Halvorsen, R: Digital freedom for persons with disabilities: Are policies to enhance e-accessibility and e-inclusion becoming more similar in the Nordic countries and the US? In: Waddington, L., Quinn, G. (eds.) European yearbook of disability law: 2. Intersentia, p. 77 (2010)

  21. Bogdanova, G., Sabev, N., Tomov, Z., Ekmekci, M.: Physical and digital accessibility in museums in the new reality. In: 2021 5th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), pp. 404–408. https://doi.org/10.1109/ISMSIT52890.2021.9604526 (2021)

  22. NDIA: Digital inclusion 101. National Digital Inclusion Alliance. https://www.digitalinclusion.org/digital-inclusion-101/

  23. Taylor, J., Mote, K.: Getting started with accessibility and inclusion. JISC. https://www.jisc.ac.uk/guides/getting-started-with-accessibility-and-inclusion (2021). Accessed 12 March 2021

  24. Tigwell, G.W.: Nuanced perspectives toward disability simulations from digital designers, blind, low vision, and color blind people. In: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, pp. 1–15. https://doi.org/10.1145/3411764.3445620 (2021)

  25. Jeong, D.: Analysis of research trends on the web-accessibility in Korea: focusing on articles published in related to disabilities, special education, rehabilitation and welfare from 2010 to 2020. J. Spec. Educ. Curric. Instr. 13(3), 231–247 (2020)

    Google Scholar 

  26. Kulkarni, M.: Digital accessibility: challenges and opportunities. IIMB Manag. Rev. 31(1), 91–98 (2019). https://doi.org/10.1016/j.iimb.2018.05.009

    Article  Google Scholar 

  27. She, L., Martin, F.: Systematic review (2000 to 2021) of online accessibility research in higher education. Am. J. Distance Educ. 36(4), 1–20 (2022). https://doi.org/10.1080/08923647.2022.2081438

    Article  Google Scholar 

  28. Botelho, F.H.F.: Accessibility to digital technology: virtual barriers, real opportunities. Assist. Technol. 33(sup1), 27–34 (2021). https://doi.org/10.1080/10400435.2021.1945705

    Article  Google Scholar 

  29. Lazar, J., Goldstein, D., Taylor, A.: Introduction to accessible technology. In: Lazar, J., Goldstein, D., Taylor, A. (eds.) Ensuring digital accessibility through process and policy, pp. 1–19. Elsevier, Amsterdam (2015). https://doi.org/10.1016/B978-0-12-800646-7.00001-0

    Chapter  Google Scholar 

  30. Ministry of Science and ICT, & National Information Society Agency: 2022 Web Accessibility Report (Web Accessibility Report, p. 183). Ministry of Science and ICT (2023)

  31. Kim, M., Kim, J.: A study on recent research trend on web accessibility evaluation in Korea. KIPS Trans. Softw. Data Eng. 7(1), 33–42 (2018). https://doi.org/10.3745/KTSDE.2018.7.1.33

    Article  Google Scholar 

  32. Eusébio, C., Silveiro, A., Teixeira, L.: Website accessibility of travel agents: An evaluation using web diagnostic tools. J. Access Des. All 10(2), 180–208 (2020). https://doi.org/10.17411/jacces.v10i2.277

    Article  Google Scholar 

  33. Park, H., Kim, K., Lee, K.: Application basics of Korean web content accessibility guidelines 2.1 to web visualization of geo-based information. J. Cadastre Land Inform. 46(2), 123–135 (2016)

    Google Scholar 

  34. Ismail, A., Kuppusamy, K.S.: Web accessibility investigation and identification of major issues of higher education websites with statistical measures: a case study of college websites. J. King Saud. Univ.—Comput. Inf. Sci. 34(3), 901–911 (2022). https://doi.org/10.1016/j.jksuci.2019.03.011

    Article  Google Scholar 

  35. Lněnička, M., Máchová, R.: A theoretical framework to evaluate ICT disparities and digital divides: challenges and implications for e-government development. Rev. Econ. Perspect. 22(1), 25–51 (2022). https://doi.org/10.2478/revecp-2022-0002

    Article  Google Scholar 

  36. Paiva, I.M., Siqueira, S., Ferreira, S.B.L.: The Windows 10’s color filter feature as an aid for color blind people in the use of websites. In: Proceedings of the XX Brazilian Symposium on Human Factors in Computing Systems, pp. 1–11. https://doi.org/10.1145/3472301.3484341 (2021)

  37. Waecker, E., Fulkerson, M., Power, J., Ku, J.: From content creation to content delivery: partnering to improve e-book accessibility. Ser. Libr. 76(1–4), 147–155 (2019). https://doi.org/10.1080/0361526X.2019.1565512

    Article  Google Scholar 

  38. Stanley, J., ten Brink, R., Valiton, A., Bostic, T., Scollan, R.: Chatbot accessibility guidance: A review and way forward. In: Yang, X.-.S, Sherratt, S., Dey, N., Joshi, A. (eds.) Proceedings of Sixth International Congress on Information and Communication Technology, vol. 216, pp. 919–942 (2022). https://doi.org/10.1007/978-981-16-1781-2_80

  39. Osolen, R.S., Brochu, L.: Creating an authentic experience: a study in comic books, accessibility, and the visually impaired reader. Int. J. Inf. Divers. Incl. 4(1), 108–118 (2019). https://doi.org/10.33137/ijidi.v4i1.32405

    Article  Google Scholar 

  40. Mambo, W.N.: Design science framework for individual innovation self-learning. World J. Innov. Res. 9(5), 165–171 (2020)

    Google Scholar 

  41. Muntean, M., Militaru, F.D.: Design science research framework for performance analysis using machine learning techniques. Electronics 11(16), 2504 (2022). https://doi.org/10.3390/electronics11162504

    Article  Google Scholar 

  42. Blanka, C., Krumay, B., Rueckel, D.: The interplay of digital transformation and employee competency: a design science approach. Technol. Forecast. Soc. Change 178, 121575 (2022). https://doi.org/10.1016/j.techfore.2022.121575

    Article  Google Scholar 

  43. Lim, C., Baba, K., Iijima, J.: Smart tourism capability maturity framework: a design science research approach. Asia Pac. J. Inf. Syst. 29(3), 503–523 (2019). https://doi.org/10.14329/apjis.2019.29.3.503

    Article  Google Scholar 

  44. Carvalho, A.: Bringing transparency and trustworthiness to loot boxes with blockchain and smart contracts. Decis. Support. Syst. 144, 113508 (2021). https://doi.org/10.1016/j.dss.2021.113508

    Article  Google Scholar 

  45. Folha, R.: Towards a novel business process model for food delivery services using blockchain technology. AIS Electron. Libr. 5, 1–10 (2022)

    Google Scholar 

  46. Kim, J., Yi, E.: A Study on the Cognitive Difference of Brand Value Delivered through Color—Focusing on Color Vision Defectives (Protanopia and Deuteranopia). DBpia, pp. 104–105. http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE10968153 (2021)

  47. Chan, X.B.V., Goh, S.M.S., Tan, N.C.: Subjects with colour vision deficiency in the community: what do primary care physicians need to know? Asia Pac. Fam. Med. 13(10), 1–10 (2014)

    Google Scholar 

  48. Kim, S.J.: A study on the effects of the shape factors of traffic signals on the improvement of signal recognition by color vision defectives. Dissertation, Hongik University (2020)

  49. Engeset, R.V., Pfuhl, G., Orten, C., Hendrikx, J., Hetland, A.: Colours and maps for communicating natural hazards to users with and without colour vision deficiency. Int. J. Disaster Risk Reduct. 76, 103034 (2022). https://doi.org/10.1016/j.ijdrr.2022.103034

    Article  Google Scholar 

  50. Reiss, M.J., Labowitz, D.A., Forman, S., Wormser, G.P.: Impact of color blindness on recognition of blood in body fluids. Arch. Intern. Med. 161(3), 461 (2001). https://doi.org/10.1001/archinte.161.3.461

    Article  Google Scholar 

  51. Flotte, T.J., Cornell, L.D.: Color vision deficiency survey in anatomic pathology. Am. J. Clin. Pathol. 158(4), 516–520 (2022). https://doi.org/10.1093/ajcp/aqac081

    Article  Google Scholar 

  52. Winters, J.E., Matchinski, T.L., Squier, K.A.: Color vision deficiency among adults attending a vision rehabilitation clinic. Optom. Vis. Perform. 5(3), 125–129 (2017)

    Google Scholar 

  53. Yoon, S.-H., Kim, H.-W., Kankanhalli, A.: What makes people watch online TV clips? An empirical investigation of survey data and viewing logs. Int. J. Inf. Manag. 59, 102329 (2021). https://doi.org/10.1016/j.i**fomgt.2021.102329

    Article  Google Scholar 

  54. Li, H., Zhang, L., Zhang, X., Zhang, M., Zhu, G., Shen, P., et al.: Color vision deficiency datasets & recoloring evaluation using GANs. Multimedia Tools Appl. 79, 27583–27614 (2020)

    Article  Google Scholar 

  55. Petrović, G., Fujita, H.: Deep correct: deep learning color correction for color blindness. Front Artif. Intell. Appl. 297, 824–834 (2017). https://doi.org/10.3233/978-1-61499-800-6-824

    Article  Google Scholar 

  56. Zhu, Z., Mao, X.: Image recoloring for color vision deficiency compensation: a survey. Vis. Comput. 37(12), 2999–3018 (2021). https://doi.org/10.1007/s00371-021-02240-0

    Article  Google Scholar 

  57. Isola, P., Zhu, J.Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 1125–1134 (2017)

  58. Kim, C., Kim, W.: Becoming a cyborg. Sakyejul (2021)

  59. Wang, T.-C., Liu, M.-Y., Zhu, J.-Y., Tao, A., Kautz, J., Catanzaro, B.: High-resolution image synthesis and semantic manipulation with conditional GANs. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 8798–8807. https://doi.org/10.1109/CVPR.2018.00917 (2018)

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Acknowledgements

This work was supported by the Ministry of Education of the Republic of Korea, the National Research Foundation of Korea (NRF-2023S1A5C2A03095169), and the Ministry of Science and ICT (MSIT) Korea, under the Information Technology Research Center (ITRC) support program (IITP-2024-2020-0-01749) supervised by the Institute of Information and Communications Technology Planning and Evaluation (IITP).

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Authors and Affiliations

  1. School of Media and Communication, Korea University, 145 Anam-Ro, Seongbuk-Gu, Seoul, 02841, South Korea

    Seungyeon Ha & Seongcheol Kim

  2. School of Industrial Management Engineering, Korea University, 145 Anam-Ro, Seongbuk-Gu, Seoul, 02841, South Korea

    Jaehoon Kim, Sanghoon Kim & Seoung Bum Kim

  3. School of Electrical Engineering, Korea University, 145 Anam-Ro, Seongbuk-Gu, Seoul, 02841, South Korea

    Guyoung Moon & Jongok Kim

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  1. Seungyeon Ha
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Contributions

Seungyeon Ha wrote the main manuscript text. Jaehoon Kim, Sanghoon Kim and Guyoung Moon developed and tested the image translation network (algorithm). Seoung Bum Kim, Jongok Kim and Seongcheol Kim reviewed the manuscript. Seongcheol Kim got the permission from the Naver Webtoon and creators.

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Correspondence to Seongcheol Kim.

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Ha, S., Kim, J., Kim, S. et al. Improving webtoon accessibility for color vision deficiency in South Korea using deep learning. Univ Access Inf Soc (2024). https://doi.org/10.1007/s10209-024-01113-2

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