Abstract
The primary goal of image color correction is to minimize color confusion for those people who experience deficiencies in their ability to distinguish certain colors. When the colors in a particular image are converted so as to make them perceivable to color vision deficient people, most of the existing methods correct all the colors of the image instead of only the specific colors that are confused. When ordinary people view the images converted using such techniques, they experience a significant difference in perception. To solve this problem, this study investigates the color perception of color vision deficient people through analysis of confused color regions in images and proposes a new method that corrects the minimum number of color regions into optimal colors. For this purpose, the proposed method builds a confusion line database for colors confused by color vision deficient people using the CIEDE2000 color-difference formula and Brettel's method for simulation of color vision deficiency in the offline stage. In the online processing stage, regions are divided through the region growing technique, and the colors in the divided images are compared. When there exist confused colors by color vision deficient people, a method for finding the optimal color is proposed through the confusion line database. Furthermore, this study developed an optimization index to propose a method of finding such optimal colors and validated them through various tests. The excellence of the color correction results of this study was demonstrated based on an objective index as well as on participants' subjective visual perception through comparative experiments with other existing studies.
Highlights
With the development of multimedia technology, we can access various types of multimedia data, such as reproduced or recorded images, videos, and voices, and these images can be reproduced and displayed with colors almost identical to their natural appearance due to advanced and high-quality display technology
Among the people with color-vision deficiency, 26% of those have protanopia, which is a disorder in the L cone cell. 72% of color vision deficient people have deuteranopia, which is a disorder in the M cone cell. and the remaining 2% have tritanopia, which is a disorder in the S cone cell [1]
EXPERIMENTAL RESULTS The correction method proposed in this study minimizes unnecessary color corrections because the most ideal color in the current image is selected for correction using a confusion line database during the color correction
Summary
With the development of multimedia technology, we can access various types of multimedia data, such as reproduced or recorded images, videos, and voices, and these images can be reproduced and displayed with colors almost identical to their natural appearance due to advanced and high-quality display technology. The proposed method performs image segmentation through region growing [21] using the hue value of pixels so that a confusion line database can be applied, thereby detecting confusing colors in images and selecting the regions to be corrected using pixel data and the confusion line database. This process helps determine whether to correct the colors in the image or the segmented sections in the image. From the viewpoint of those who are colorblind, the corrected color obtained from the correction process is a color that is not confused with other color groups, and it becomes a color that is easiest to distinguish from other color groups in the image
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