Xiuwen Liu, DeLiang Wang
A figure-ground segregation network is proposed based on a novel boundary pair representation. Nodes in the network are bound(cid:173) ary segments obtained through local grouping. Each node is ex(cid:173) citatorily coupled with the neighboring nodes that belong to the same region, and inhibitorily coupled with the corresponding paired node. Gestalt grouping rules are incorporated by modulating con(cid:173) nections. The status of a node represents its probability being figural and is updated according to a differential equation. The system solves the figure-ground segregation problem through tem(cid:173) poral evolution. Different perceptual phenomena, such as modal and amodal completion, virtual contours, grouping and shape de(cid:173) composition are then explained through local diffusion. The system eliminates combinatorial optimization and accounts for many psy(cid:173) chophysical results with a fixed set of parameters.