ACM Home Page
Please provide us with feedback. Feedback
Adapting palettes to color vision deficiencies by genetic algorithm
Full text PdfPdf (1.23 MB)
Source
Genetic And Evolutionary Computation Conference archive
Proceedings of the 10th annual conference on Genetic and evolutionary computation table of contents
Atlanta, GA, USA
SESSION: Genetic algorithms papers table of contents
Pages 1065-1072  
Year of Publication: 2008
ISBN:978-1-60558-130-9
Authors
Luigi Troiano  University of Sannio, Benevento, Italy
Cosimo Birtolo  Poste Italiane, Napoli, Italy
Maria Miranda  University of Sannio, Benevento, Italy
Sponsors
ACM: Association for Computing Machinery
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 11,   Downloads (12 Months): 86,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1389095.1389291
What is a DOI?

ABSTRACT

In choosing a color palette, it is necessary to take into the account the needs of color vision impaired users, in order to make information and services accessible to a broader audience. This means to search the space of color palettes aimed to find a color combination representing a good trade-off between aesthetics and accessibility requirements. In this paper, we present a solution based on genetic algorithms. Experimental results highlight this approach to be an efficient but effective way to assist UI designers by suggesting appropriate variations of color palettes.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Web content accessibility guidelines 2.0. Technical Report 11, W3C, December 2007.
 
2
H. Brettel, F. Viénot, and J. D. Mollon. Computerized simulation of color appearance for dichromats. J. Opt. Soc. Am. A, 14(10):2647--2655, 1997.
 
3
D. R. Commission. The Web: Access and Inclusion for Disabled People. April 2004. ISBN 0-11-703287-5.
 
4
J. D. M. Françoise Viénot, Hans Brettel. Digital video colourmaps for digital video colourmaps for displays by dichromats. Color Research and Application, 24(4):243--251, 1999.
 
5
 
6
M. Gradisar, I. Humar, and T. Turk. The legibility of colored web page texts. Information Technology Interfaces, 2007. ITI 2007. 29th International Conference on, pages 233--238, 25-28 June 2007.
 
7
M. Ichikawa, K. Tanaka, S. Kondo, K. Hiroshima, K. Ichikawa, S. Tanabe, and K. Fukami. Web-page color modification for barrier-free color vision with genetic algorithm. In E. Cantú-Paz, J. A. Foster, K. Deb, L. Davis, R. Roy, U.-M. O'Reilly, H.-G. Beyer, R. K. Standish, G. Kendall, S. W. Wilson, M. Harman, J. Wegener, D. Dasgupta, M. A. Potter, A. C. Schultz, K. A. Dowsland, N. Jonoska, and J. F. Miller, editors, GECCO, volume 2724 of Lecture Notes in Computer Science, pages 2134--2146. Springer, 2003.
8
9
 
10
K. Knoblauch, A. Arditi, and J. Szlyk. Effects of chromatic and luminance contrast on reading. J. Opt. Soc. Am. A, 8(2):428, 1991.
 
11
G. E. Legge, D. H. Parish, A. Luebker, and L. H. Wurm. Psychophysics of reading. xi. comparing color contrast and luminance contrast. J. Opt. Soc. Am. A, 7(10):2002, 1990.
 
12
M. Ou-Yang and S.-W. Huang. Design considerations between color gamut and brightness for multi-primary color displays. Display Technology, Journal of, 3(1):71--82, March 2007.
 
13
 
14
V. Smith and J. Pokorny. Spectral sensitivity of the foveal cone photopigments between 400 and 500 nm. Vision Res, 15(2):161--71, 1975.
 
15
H. Takagi. Interactive evolutionary computation: fusion of the capabilities of ec optimization and human evaluation. Proceedings of the IEEE, 89(9):1275--1296, Sep 2001.
 
16

Collaborative Colleagues:
Luigi Troiano: colleagues
Cosimo Birtolo: colleagues
Maria Miranda: colleagues