DocumentCode :
3426844
Title :
Affine layer segmentation and adjacency graphs for vortex detection
Author :
Heroor, Shravan ; Cohen, Isaac
Author_Institution :
Inst. for Robotics & Intelligent Syst., Southern California Univ., CA, USA
Volume :
4
fYear :
2004
fDate :
23-26 Aug. 2004
Firstpage :
223
Abstract :
In This work we review and present different methods for the detection and characterization of vortices. Our algorithm works on the segmentation of the image into affine layers. These layers are computed using a parametric tensor voting and encoded in an adjacency graph. Paths are computed from the adjacency graph and are used for characterizing paths´ properties such as: critical points and vortices. We illustrate the proposed approach to a satellite image sequence of water vapor in the atmosphere.
Keywords :
graph theory; image segmentation; image sequences; object detection; tensors; adjacency graphs; affine layer segmentation; parametric tensor voting; satellite image sequence; vortex detection; Image segmentation; Image sequences; Intelligent robots; Motion estimation; Ocean temperature; Satellites; Sea surface; Streaming media; Tensile stress; Voting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-2128-2
Type :
conf
DOI :
10.1109/ICPR.2004.1333744
Filename :
1333744
Link To Document :
بازگشت