title: Predicting the readability of transparent text.
abstract: Will a simple global masking model based on image detection be successful at predicting the readability of transparent text? Text readability was measured for two types of transparent text: additive (as occurs in head-up displays) and multiplicative (which occurs in see-through liquid crystal display virtual reality displays). Text contrast and background texture were manipulated. Data from two previous experiments were also included (one using very low contrasts on plain backgrounds, and the other using higher-contrast opaque text on both plain and textured backgrounds). All variables influenced readability in at least an interactive manner. When there were background textures, the global masking index (that combines text contrast and background root mean square contrast) was a good predictor of search times (r = 0.89). When the masking was adjusted to include the text pixels as well as the background pixels in computations of mean luminance and contrast variability, predictability improved further (r = 0.91).
authors.affiliation: Department of Psychology, Stephen F. Austin State University, Nacogdoches, TX, USA. lscharff@sfasu.edu
authors.forename: Lauren F V
authors.initials: LF
authors.lastname: Scharff
authors.forename: Albert J
authors.initials: AJ
authors.lastname: Ahumada
mesh_terms: D000293:Adolescent; D000328:Adult; D015350:Contrast Sensitivity / Q000502:physiology*; D006801:Humans; D008027:Light; D008875:Middle Aged; D008954:Models, Biological; D010470:Perceptual Masking / Q000502:physiology*; D011932:Reading; D014785:Vision, Ocular / Q000502:physiology; D014796:Visual Perception / Q000502:physiology*