Using letter
identifiability to predict readability
of transparent
text on textured backgrounds
L. F. V.
Scharff
Stephen F. Austin State
University, Nacogdoches, TX
A. J. Ahumada
NASA Ames Research Center,
Moffett Field, CA
Abstract
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 ,
Hill, & Ahumada, Optics Express, 2000). More recently (ARVO, 2001;
JOV, in press),
we showed that an adjusted version of this same measure was able to predict
readability using different types of text transparency (additive v.
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.
Funding for this work was
provided by the Airspace Operations Systems (AOS) Project of NASA's Airspace
Systems Program.