Title :
Perceptual grouping based on fuzzy sets
Author :
Kang, Hang-Bong ; Walker, Ellen L.
Author_Institution :
Rensselaer Polytech. Inst., Troy, NY, USA
Abstract :
The authors propose a new approach based on fuzzy sets for detecting relations among points, line segments, and elliptic arc segments. Appropriate constraints defining the relations are extracted. A suitable fuzzy membership function is assigned to each constraint. Then the constraints are combined by fuzzy set operations to describe meaningful relations. According to these meaningful relations, a perceptual grouping is executed. Grouping methods are described on the basis of collinear and coelliptic relations. A measure of the significance of grouping for high-level vision processing is discussed. A prototype system for perceptual grouping from image data was implemented using a frame-based knowledge representation scheme, and experimental results for real image data are presented
Keywords :
edge detection; feature extraction; fuzzy set theory; geometry; image segmentation; coelliptic relations; collinear relations; edge detection; elliptic arc segments; feature extraction; frame-based knowledge representation; fuzzy membership function; fuzzy sets; high-level vision processing; image segmentation; line segments; perceptual grouping; points; Computer science; Concurrent computing; Data mining; Fuzzy sets; Image edge detection; Image segmentation; Knowledge representation; Parallel processing; Prototypes; Systems engineering and theory;
Conference_Titel :
Fuzzy Systems, 1992., IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-0236-2
DOI :
10.1109/FUZZY.1992.258737