title: Curve detection in a noisy image.
abstract: In this paper we propose a new theory of the Gestalt law of good continuation. In this theory perceptual processes are modeled by an exponential pyramid algorithm. To test the new theory we performed three experiments. The subject's task was to detect a target (a set of dots arranged along a straight or curved line) among background dots. Detectability was high when: (a) the target was long; (b) the density of target dots relative to the density of background dots was large; (c) the local change of angle was small along the entire line; (d) local properties of the target were known to the subject. These results are consistent with our new model and they contradict prior models.
authors.affiliation: Department of Psychological Sciences, Purdue University, West Lafayette, IN 47907-1364, USA. pizlo@psych.purdue.edu
authors.forename: Z
authors.initials: Z
authors.lastname: Pizlo
authors.forename: M
authors.initials: M
authors.lastname: Salach-Golyska
authors.forename: A
authors.initials: A
authors.lastname: Rosenfeld
mesh_terms: D000465:Algorithms; D005260:Female; D005863:Gestalt Theory; D006801:Humans; D008297:Male; D008959:Models, Neurological; D010364:Pattern Recognition, Visual / Q000502:physiology; D011601:Psychophysics; D014792:Visual Acuity; D014796:Visual Perception / Q000502:physiology*