Supervised Classification of Early Perceptual Structure in Dot Patterns*
نویسندگان
چکیده
A supervised algorithm for computing perceptual groupings in dot patterns is presented. The algorithm uses shape features of the polygons in the Voronoi tessellation of the input pattern. The training patterns identified b y humans are used to obtain an initial noncontextual classification which is then refined b y a probabilistic relaxation labeling.
منابع مشابه
Extraction of early perceptual structure in dot patterns: Integrating region, boundary, and component gestalt
This paper presents a computational approach to extracting basic perceptual structure, or the lowest level grouping in dot patterns. The goal is to extract the perceptual segments of dots that group together because of their relative locations. The dots are interpreted as belonging to the interior or the border of a perceptual segment, or being along a perceived curve, or being isolated. To per...
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تاریخ انتشار 1992