Development and validation of icons varying in their abstractness

Confounds in pictorial sets: The role of complexity and familiarity in basic-level picture processing

“…The extent to which an image is measured as having edges correlated highly with subjective judgments of image complexity. For example, the perimeter detection metric correlated (r. = .64,p < .001) with a random set (n = 68) of the McDougall et al icons and symbols and also correlated (r = .66, p < .001) with measures in Garcia et al (1994). This perimeter metric has reasonably good predictive validity when applied to other pictorial images (Forsythe, Sheehy, & Sawey, 2003a).…”

Measuring icon complexity: An automated analysis

“…The function measures were correlated with metrics developed by Garcia et al (1994) and McDougall et al (1999). High correlations would indicate similar measurements of icon complexity.…”

“…McDougall et al (1999) has reported on the success of one semi-automated system of icon measurement. Garcia, Badre, and Stasko (1994) developed a technique based on a calculation of several icon features, including the number of closed and open figures and horizontal and vertical lines. This metric was developed primarily as a measure of icon concreteness, and, using this measure, Garcia et al reported that icons that are pictorially similar to their realworld counterparts are more likely to be judged as complex.…”

“…An automated system capable of producing reliable estimates of perceived complexity could reduce development costs and time. Measures of icon complexity developed by Garcia, Badre, and Stasko (1994) and McDougall, Curry, and de Bruijn (1999) were correlated with six icon properties measured using Matlab (MathWorks, 2001) software, which uses image-processingtechniques to measure icon properties. The six icon properties measured were icon foreground, the number of objects in an icon, the number of holes in those objects, and two calculations of icon edges and homogeneity in icon structure.…”

Lisbon Symbol Database (LSD): Subjective norms for 600 symbols

“…Despite the proposed objective metrics to define the visual complexity of pictorial stimuli (e.g., the size of the digitalized stimulus picture files, as in the International Picture Naming Project-Székely & Bates, 2000; or the number of lines, letters, or simple shapes that an icon contains- Garcia, Badre, & Stasko, 1994; for a review, see Forsythe et al, 2008), visual complexity is often measured in subjective terms. In this case, the instructions must emphasize that participants should indicate the complexity level of the visual characteristics of the symbols and not the complexity level of the object or concept they depict (e.g., Alario & Ferrand, 1999;Bonin et al, 2003;Isherwood et al, 2007;McDougall et al, 1999;Sanfeliu & Fernandez, 1996;Snodgrass & Vanderwart, 1980).…”