DocumentCode :
2609442
Title :
Finding convex edge groupings in an image
Author :
Huttenlocher, Daniel P. ; Wayner, Peter C.
Author_Institution :
Dept. of Comput. Sci., Cornell Univ., Ithaca, NY, USA
fYear :
1991
fDate :
3-6 Jun 1991
Firstpage :
406
Lastpage :
412
Abstract :
A method for identifying groups of intensity edges in an image that are likely to result from the same convex object in a scene is described. A key property of the method is that its output is no more complex than the original image. The method uses a triangulation of linear edge segments to define a local neighborhood that is scale invariant. From this local neighborhood a local convexity graph that encodes which neighboring image edges could be part of a convex group of image edges is constructed. A path in the graph corresponds to a convex polygonal chain in the image, such as a convex polygon or a spiral. Examples are presented to illustrate that the technique find intuitively salient groups
Keywords :
computational geometry; computer vision; computerised picture processing; convex edge groupings; convex polygonal chain; encoding; intensity edges; linear edge segments; local convexity graph; local neighborhood; scale invariant; triangulation; Computational complexity; Computer science; Filtering; Image recognition; Image segmentation; Jacobian matrices; Layout; Shape; Spirals; Statistical analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1991. Proceedings CVPR '91., IEEE Computer Society Conference on
Conference_Location :
Maui, HI
ISSN :
1063-6919
Print_ISBN :
0-8186-2148-6
Type :
conf
DOI :
10.1109/CVPR.1991.139724
Filename :
139724
Link To Document :
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