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Lauren Scharff, Albert J. Ahumada; Using letter identifiability to predict readability of transparent text on textured background. Journal of Vision 2002;2(10):137. doi: 10.1167/2.10.137.
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© ARVO (1962-2015); The Authors (2016-present)
It would be useful to have measures that predict the effects of background contrast variations on text readability. Our previous work showed that a combination of the overall text contrast and the background contrast energy provided a useful measure (Scharff & Ahumada, Optics Express, 2000). More recently (ARVO, 2001), we showed that an adjusted version of this same measure was able to predict readability using different types of text transparency (additive vs. multiplicative text combinations with the background). The adjusted measure uses both the text and the background to compute the text contrast and the masking RMS contrast. In that study, there were three experimental factors: text contrast (0.30, 0.45), transparency combination rule (additive, multiplicative), and masking pattern (uniform, “wave”, “culture”). The two patterns were used in prior experiments and were originally obtained from a web site providing backgrounds for web designers. They were adjusted to have the same mean luminance, but they had different RMS contrasts (0.27 and 0.15, respectively). While the adjusted measure did correctly predict the effects of transparency, it incorrectly predicted more masking by the “wave” pattern. Subsequent analyses indicate that adding spatial frequency selectivity or masking local to the location of the target words does not improve predictability of the pattern differences. For the current study, we measured participants' ability to identify the individual letters shown with their backgrounds as presented in the earlier study. It is predicted that, although the wave pattern had a larger background RMS contrast, many individual letters were not affected by the background pattern, and thus, assuming some clear letters are better than all somewhat masked letters, masking should be less than predicted by the metric.
Scharff, L. V., Hill, A. L., and Ahumada, A. J. (2000). Discriminability measures for predicting readability of text on textured backgrounds. Optics Express, Vol 6 (4), pp. 81–91, http://epubs.osa.org/oearchive/source/19007.htm
Scharff, L. V. & Ahumada, A. J. (2001). Predicting Readability of Transparent Text on Textured Backgrounds. Investigative Ophthalmology and Visual Science, 42, S733.
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