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ARIS - Adaptive Rendering of Interfaces and Shades

5.0(

5 ratings

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Overview

Enhancing color recognition through Daltonization algorithms for color-blind users.

ARIS is developed by Jellienne Sagun, Katrina Leigh Lipata, Jiecel Pascua and Marry Glo Sanchez as part of a thesis project in Computer Science, focusing on improving digital accessibility through adaptive rendering techniques. This extension is intended for educational and research purposes only. To ensure the effectiveness of ARIS in enhancing color perception for individuals with color vision deficiency (CVD), we have included a test image generated using the ColorBlindTestGenerator by Tucker87. This tool allows users to assess their ability to distinguish colors before and after applying ARIS' Daltonization filters. All rights to the original test generator remain with the respective developer. Color deficiency matrices were adapted from the model proposed by Machado et al. in "A Physiologically-based Model for Simulation of Color Vision Deficiency" (IEEE Transactions on Visualization and Computer Graphics, 2009). More info: http://www.inf.ufrgs.br/~oliveira/pubs_files/CVD_Simulation/CVD_Simulation.html The test image included in ARIS was generated using the ColorBlindTestGenerator by Tucker87: https://github.com/tucker87/ColorBlindTestGenerator/

Details

  • Version
    1.4
  • Updated
    June 29, 2025
  • Size
    62.28KiB
  • Languages
    English (United States)
  • Developer
    Email
    jelieyss25@gmail.com
  • Non-trader
    This developer has not identified itself as a trader. For consumers in the European Union, please note that consumer rights do not apply to contracts between you and this developer.

Privacy

ARIS - Adaptive Rendering of Interfaces and Shades has disclosed the following information regarding the collection and usage of your data. More detailed information can be found in the developer's privacy policy.

ARIS - Adaptive Rendering of Interfaces and Shades handles the following:

Website content

This developer declares that your data is

  • Not being sold to third parties, outside of the approved use cases
  • Not being used or transferred for purposes that are unrelated to the item's core functionality
  • Not being used or transferred to determine creditworthiness or for lending purposes

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