DocumentCode :
301746
Title :
Learning perceptual organization for straight line segments
Author :
Ralescu, Anca L. ; Shanahan, James G.
Author_Institution :
Lab. for Int. Fuzzy Eng., Yokohama, Japan
Volume :
4
fYear :
1995
fDate :
22-25 Oct 1995
Firstpage :
3600
Abstract :
Address the problem of structure inference in an image, in the framework of perceptual organization. This paper describes work in progress which builds on a subset of the authors´ previous work on fuzzy perceptual grouping. More precisely, the authors are concerned with obtaining a fuzzy system which can achieve grouping of line segments. The data are obtained from images and consist of the results of edge extraction to which a line segment fitting algorithm has been applied. For each collection of similar and collinear segments used as input, a representative segment is used to summarize this collection. In the training stage both the input collection and the output segment can be either indicated by a human user, or obtained by overlaying the segment and real images
Keywords :
fuzzy set theory; image recognition; image segmentation; collinear segments; edge extraction; fuzzy perceptual grouping; fuzzy system; line segment fitting algorithm; perceptual organization; straight line segments; structure inference; training stage; Cameras; Fuzzy sets; Fuzzy systems; Image segmentation; Modeling; Parameter estimation; Robustness; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-2559-1
Type :
conf
DOI :
10.1109/ICSMC.1995.538346
Filename :
538346
Link To Document :
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