USER'S PREFERENCE-BASED COLOR TRANSFORMATION USING INTERACTIVE GENETIC ALGORITHM [article]

Hang-Bong Kang, Hye-Yoon Woo
<span title="">2010</span> <i title="The Eurographics Association"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xgoygnj3knbt3jsqqs5uay37ba" style="color: black;">Eurographics State of the Art Reports</a> </i> &nbsp;
In this paper, we propose a new color transform method in the image based on the user's preferences. To obtain general preferences for color, we first divided the images into two categories as favourable and unfavourable groups based on the users' evaluation. From the categorized groups of images, we compute color histograms to construct general templates for 8 primary colors. To reflect the user's own preference in the color perception, we adopted an interactive genetic algorithm. In the
more &raquo; ... ctive genetic algorithm, each individual consists of three chromosomes for H, S, and V and the fitness value is computed from the user's input, which is then used as criteria to iterate Genetic Algorithm for learning the user's preference. Finally, a personalized individual is generated. By transforming the colors in the image with the personalized individual, a re-colorred image is generated according to the user own preference. Survey results show that re-colorred images from our proposed personalized color templates are more satisfying than the original images.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2312/egp.20101027">doi:10.2312/egp.20101027</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iz66vmyxnbdtpicfl67ohfpgxm">fatcat:iz66vmyxnbdtpicfl67ohfpgxm</a> </span>
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