Perceptual organization of two-dimensional patterns.

Abstract

The perceptual organization of image patterns is considered from 2 standpoints. First, a theoretical framework is presented from which computational models of perceptual organization can be constructed and tested. Second, a specific computational model for perceptual organization of line images is described. In this model, input images are first processed by a dense array of neurons that have properties consistent with recent analyses of single-neuron responses in primary visual cortex. Then, complex image structure is discovered by interleaved pattern-matching and grouping processes constrained by a generalized uniqueness principle. A series of 3-pattern grouping experiments was performed to test a restricted version of the model and to estimate critical parameters. Using the estimated parameters, an extended version of the model was tested by generating predictions for a series of "textbook" perceptual organization demonstrations.