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Journal Articles Pattern Recognition Year : 2008

Combining local belief from low-level primitives for perceptual grouping


Segmentation is usually unable to cope with artifacts due to slight change in lighting conditions or object occlusion for instance. That is why perceptual grouping is often used to overcome segmentation’s lacks. This refers to the ability of human visual system to impose structure and regularity over signal-based data. Gestalt psychologists have exhibited some properties which are used during perceptual grouping, such as proximity, continuity, or symmetry. Then, some implementations of these have been proposed in computer vision. However, most of these works rely on contour-based primitives. Besides, they often use one single property to merge close regions, which may not be sufficiently robust. We propose a new framework for bottom-up perceptual grouping, which relies on a region-based segmentation. It allows us to use region or contour information, when it is the most suitable. Besides, we propose to trigger a grouping when several Gestalt properties support it. This could increase the robustness of perceptual grouping. We use Dempster–Shafer theory to combine the influence of several Gestalt properties over each grouping, as it is especially designed for this. We also present numerous promising results, which show the efficiency of our approach.

Dates and versions

hal-01500315 , version 1 (03-04-2017)



Nicolas Zlatoff, Bruno Tellez, Atilla Baskurt. Combining local belief from low-level primitives for perceptual grouping. Pattern Recognition, 2008, 4, 41, pp.1215-1229. ⟨10.1016/j.patcog.2007.07.006⟩. ⟨hal-01500315⟩
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