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W e consider the problem of detecting global symmetry in images consisting of dense arrangements of local features, such as dots or oriented segments. Images of this kind are encountered in textured scenes or field-type pictorial representations. The proposed computational model, elaborated on the basis of several psychophysical experiments, assumes a precedence of grouping over symmetry detection and consists of three stages: (1) a grouping stage in which clusters are formed among local elements presenting a suficient level of mutual afinity, (2) a symmetry detection stage i n which pairs of symmetrical clusters are discovered and their axes of symmetry determined, (5') a symmetry subsumption stage in which a n attempt is made t o detect more global symmetries. A n implementataon of the model is described, and resutts are presented, showing a good agreement of the model's performance with human symmetry perception.

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