Segmentation of objects from backgrounds in visual search tasks
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Updated: Sep 28, 2026

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Published on: August 13, 2014
Jeremy M Wolfe1, Aude Oliva, Todd S Horowitz
1Center for Ophthalmic Research, Brigham and Women's Hospital, USA. wolfe@search.bwh.harvard.edu
Abstract:
In most visual search experiments in the laboratory, objects are presented on an isolated, blank background. In most real world search tasks, however, the background is continuous and can be complex. In six experiments, we examine the ability of the visual system to separate search items from a background. The results support a view in which objects are separated from backgrounds in a single, preattentive step. This is followed by a limited-capacity search process that selects objects that might be targets for further identification. Identity information regarding the object's status (target or distractor) then accumulates through a limited capacity parallel process. The main effect of background complexity is to slow the accumulation of information in this later recognition stage. It may be that recognition is slowed because background noise causes the preattentive segmentation stage to deliver less effectively segmented objects to later stages. Only when backgrounds become nearly identical to the search objects does the background have the effect of slowing item-by-item selection.
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