Improving Discrimination in Color Vision Deficiency by Image Re-Coloring

• Published in: Sensors (Basel, Switzerland) Vol. 19; no. 10; p. 2250
• Main Authors: Lin, Huei-Yung, Chen, Li-Qi, Wang, Min-Liang
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 15.05.2019; MDPI
• Subjects: Color blindness; Color vision; color vision deficiency; Coloring; Computer simulation; Eigenvectors; Electrical engineering; Genes; Image enhancement; image re-coloring; International conferences; Pigments; Separation; visual assistance; Canada; Taiwan; visual assistance; color vision deficiency; image re-coloring
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s19102250

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 λ , , 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.