Improving Discrimination in Color Vision Deficiency by Image Re-Coloring
Department of Electrical Engineering, Advanced Institute of Manufacturing with High-Tech Innovation, National Chung Cheng University, Chiayi 621, Taiwan
Department of Electrical Engineering, National Chung Cheng University, Chiayi 621, Taiwan
Asian Institute of TeleSurgery/IRCAD-Taiwan, Changhua 505, Taiwan
Author to whom correspondence should be addressed.
Received: 19 April 2019 / Revised: 8 May 2019 / Accepted: 13 May 2019 / Published: 15 May 2019
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People with color vision deficiency (CVD) cannot observe the colorful world due to the damage of color reception nerves. In this work, we present an image enhancement approach to assist colorblind people to identify the colors they are not able to distinguish naturally. An image re-coloring algorithm based on eigenvector processing is proposed for robust color separation under color deficiency transformation. It is shown that the eigenvector of color vision deficiency is distorted by an angle in the
color space. The experimental results show that our approach is useful for the recognition and separation of the CVD confusing colors in natural scene images. Compared to the existing techniques, our results of natural images with CVD simulation work very well in terms of RMS, HDR-VDP-2 and an IRB-approved human test. Both the objective comparison with previous works and the subjective evaluation on human tests validate the effectiveness of the proposed method.
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MDPI and ACS Style
Lin, H.-Y.; Chen, L.-Q.; Wang, M.-L. Improving Discrimination in Color Vision Deficiency by Image Re-Coloring. Sensors 2019, 19, 2250.
Lin H-Y, Chen L-Q, Wang M-L. Improving Discrimination in Color Vision Deficiency by Image Re-Coloring. Sensors. 2019; 19(10):2250.
Lin, Huei-Yung; Chen, Li-Qi; Wang, Min-Liang. 2019. "Improving Discrimination in Color Vision Deficiency by Image Re-Coloring." Sensors 19, no. 10: 2250.
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