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Prediction of simultaneous contrast between map colors with Hunt's model of color appearance
Author(s) -
Brewer Cynthia A.
Publication year - 1996
Publication title -
color research and application
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.393
H-Index - 62
eISSN - 1520-6378
pISSN - 0361-2317
DOI - 10.1002/(sici)1520-6378(199606)21:3<221::aid-col4>3.0.co;2-u
Subject(s) - lightness , contrast (vision) , color space , artificial intelligence , set (abstract data type) , color model , perception , mathematics , selection (genetic algorithm) , color vision , task (project management) , computer vision , color contrast , color balance , pattern recognition (psychology) , computer science , psychology , color image , image (mathematics) , engineering , image processing , systems engineering , neuroscience , programming language
The objective of this research was development of a quantitative model of simultaneous contrast (induction) to aid selection of sets of easily identified map colors. The model is an extension of R. W. G. Hunt's model of color appearance. Contrasts between central and proximal colors were used to adjust Hunt's lightness, relative redness‐greenness, and relative yellowness‐blueness measures. Human subject responses to CRT displays in an experiment were analyzed to produce a set of rules for selecting map colors. Rather than predict average perceptions for central/proximal color combinations, acknowledgment was made of the inherent variability in map readers' perceptions of color by developing generalized perception buffers that accounted for at least 90% of test subject responses. The task of selecting colors that will not be confused once they appear with numerous proximal colors on a map thus becomes a task of selecting colors that do not have buffers that overlap in color space. © 1996 John Wiley & Sons, Inc.