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International Journal of Machine Learning and Cybernetics
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19-09-2024 | Original Article

Image recoloring for multiple types of Color Vision Deficiency

Authors: Xin Jin, Dandan Li, Yiqing Rong, Dongqing Zou, Wu Zhou, Xiaokun Zhang

Published in: International Journal of Machine Learning and Cybernetics | Issue 3/2025

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Abstract

The article delves into the problem of Color Vision Deficiency (CVD), also known as color blindness, and its impact on individuals' ability to perceive colors accurately. It introduces a novel image recoloring technique that uses computer vision and deep learning to improve color perception for colorblind individuals. The method involves generating recommended color palettes and adjusting image colors to enhance naturalness and harmonization. The authors demonstrate the effectiveness of their approach through objective and subjective evaluations, showcasing its superiority over existing methods. The article also includes a comprehensive review of related work in palette-based color manipulation, image recoloring for colorblindness, and colorblind simulation, providing a solid foundation for the proposed method. The method's robustness is further validated through experiments on different datasets, highlighting its potential for practical applications in assistive technologies for colorblind individuals.
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Metadata
Title
Image recoloring for multiple types of Color Vision Deficiency
Authors
Xin Jin
Dandan Li
Yiqing Rong
Dongqing Zou
Wu Zhou
Xiaokun Zhang
Publication date
19-09-2024
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 3/2025
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-024-02360-8

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