The human visual system uses a global closure mechanism

Abstract

Research asserting that the visual system instantiates a global closure heuristic in contour integration has been challenged by an argument that behaviorally-detected closure enhancement could be accounted for by low-level local mechanisms driven by collinearity or "good continuation" interacting with proximity. The present study investigated this issue in three experiments. Exp. 1 compared the visibility of closed and open contours using circles and S-contours from low to moderately high angles of path curvature in a temporal alternative-forced choice task. Circles were more detectable than S-contours, an effect that increased with curvature. The closure enhancement observed can, however, be explained by the fact that circles contain more 'contiguity' than S-contours. Additional tests added discontinuities to otherwise closed paths to control for the effects of good continuation and closure independently. Exp. 2 compared the visibility of incomplete circles (C-contours) and S-contours derived from the full circles and S-contours in Exp. 1. Exp. 3a compared the visibility of arc pairs arranged in an enclosed position similar to "()" and a non-enclosed position similar to ")(". Results consistently showed enhanced visibility of contour configurations enclosing a region even after controlling for differences in contiguity and changes of curvature direction. A control test (Exp. 3b) demonstrated that the gap in the contours of Exp. 3a was too large to be bridged by local-level collinearity/proximity alone. The combination of good continuation and proximity alone does not explain the closure effects observed across these tests, as demonstrated through the application of a Bayesian model of collinearity and proximity (Geisler et al., 2001) to the stimuli in Exps. 3a and 3b. These results argue for the presence of a global closure-driven contour enhancing mechanism in human vision.

The development of contour processing: evidence from physiology and psychophysics

“…Psychophysical studies show that adults exhibit a closure superiority effect ; that is, detectability of closed figures is enhanced relative to open figures (Kovács and Julesz, 1993; Mathes and Fahle, 2007; Machilsen and Wagemans, 2011; Gerhardstein et al, 2012). For instance, using a contour detection task with adults, Kovács and Julesz (1993) incrementally added co-aligned elements to a circular contour and found that performance was not enhanced until the contour was closed.…”

“…Closure therefore elicited a pop-out effect, by their interpretation. While there has been some contention regarding whether a global heuristic such as closure needs to be invoked to explain the closure superiority effect (Tversky et al, 2004), recent research (Gerhardstein et al, 2012) strongly suggests that such a mechanism does operate in the visual system. By separately manipulating collinearity and closure using circles and S contours, Gerhardstein et al (2012) showed that closure enhances detectability of a contour separate from local grouping heuristics.…”

“…Closure facilitates contour integration (Pettet et al, 1998; Mathes and Fahle, 2007; Gerhardstein et al, 2012), object detection (Machilsen and Wagemans, 2011), texture-segmentation (Atkinson and Braddick, 1992; Norcia et al, 2005; Machilsen and Wagemans, 2011), and figure-ground segmentation (Field et al, 1993; Kovács and Julesz, 1993; Kovács, 1996). To date, few studies have explored the development of such a closure mechanism across childhood (Gerhardstein et al, 2004; Hadad and Kimchi, 2006; Baker et al, 2008; Hadad et al, 2010a; Hipp et al, 2014).…”

Age‐related changes in visual contour integration: Implications for physiology from psychophysics

“…Contour integration studies typically present a set of collinear Gabor elements embedded in randomly oriented noise elements. Detection difficulty varies as a function of the extent of collinearity between contour elements (a straight line is easiest, Field et al, ; Hadad, Maurer, & Lewis, ), relative noise density (contours denser than or equal to surrounding noise are easier to detect; Kovács, ), eccentricity (Lev & Polat, ; Shani & Sagi, ) and closure (closed contours are easier to detect than open ones; Gerhardstein, Tse, Dickerson, Hipp, & Moser, ; Kovács, ; Kovács & Julesz, ).…”

A shape-level flanker facilitation effect in contour integration and the role of shape complexity

“…Studies have also examined how grouping of local elements into a contour is further modulated by features arising on a larger scale. Factors such as the convexity or curvature of the contour (Bertamini & Wagemans, 2013), contour closure (Elder & Zucker, 1993;Gerhardstein, Tse, Dickerson, Hipp, & Moser, 2012;Kovacs & Julesz, 1993), symmetry (Machilsen, Pauwels and Wagemans, 2009); shape familiarity and predictability (Nygard, Sassi & Wagemans, 2011;Sassi et al, 2010Sassi et al, , 2014Sassi, Machilsen, & Wagemans, 2012) have all been shown to affect grouping or contour integration.…”