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When the boundary of a familiar object is shown by a series of isolated dots,humans can often recognize the object with ease. This ability can be sustainedwith addition of distracting dots around the object. However, such capabilityhas not been reproduced algorithmically on computers. We introduce a newalgorithm that groups a set of dots into multiple non-disjoint subsets. Itconnects the dots into a spanning tree using the proximity cue. It then appliesthe straight polygon transformation to an initial polygon derived from thespanning tree. The straight polygon divides the space into polygons recursivelyand each polygon can be viewed as grouping of a subset of the dots. The numberof polygons generated is O($n$). We also introduce simple shape selection andrecognition algorithms that can be applied to the grouping result. We used bothnatural and synthetic images to show effectiveness of these algorithms.

Grouping and Recognition of Dot Patterns with Straight Offset Polygons