caa a22 4500 469036087 CHVBK 20180323132756.0 cr unu---uuuuu 170328e19920701xx s 000 0 eng 10.1007/BF00126398 doi (NATIONALLICENCE)springer-10.1007/BF00126398 Finding convex edge groupings in an image [Elektronische Daten] [Daniel Huttenlocher, Peter Wayner] In an image, there are groups of intensity edges that are likely to have resulted from the same convex object in a scene. A new method for identifying such groups is described here. Groups of edges that form a convex polygonal chain, such as a convex polygon or a spiral, are extracted from a set of image edge fragments. A key property of the method is that its output is no more complex than the original image. The method uses a triangulation of the linear edge segments in an image to define a local neighborhood that is scale invariant. From this local neighborhood a local convexity graph is constructed; this encodes which neighboring image edges could be part of a convex group. A path in the graph corresponds to a convex polygonal chain in the image, with a cyclic path corresponding to a polygon. We have implemented the method and found that it is efficient in practice as well as in theory. Examples are presented to illustrate that the technique finds intuitively salient groups, including for images of cluttered scenes. Kluwer Academic Publishers, 1992 Huttenlocher Daniel Computer Science Department, Cornell University, 14853, Ithaca, NY aut Wayner Peter Computer Science Department, Cornell University, 14853, Ithaca, NY aut International Journal of Computer Vision Kluwer Academic Publishers 8/1(1992-07-01), 7-27 0920-5691 8:1<7 1992 8 11263 https://doi.org/10.1007/BF00126398 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00126398 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Huttenlocher Daniel Computer Science Department, Cornell University, 14853, Ithaca, NY aut NATIONALLICENCE 700 1- Wayner Peter Computer Science Department, Cornell University, 14853, Ithaca, NY aut NATIONALLICENCE 773 0- International Journal of Computer Vision Kluwer Academic Publishers 8/1(1992-07-01), 7-27 0920-5691 8:1<7 1992 8 11263 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer