DocumentCode :
3328868
Title :
Dynamic segmentation for image information mining
Author :
Masi, Giuseppe ; Gaetano, Raffaele ; Scarpa, Giuseppe ; Poggi, Giovanni
Author_Institution :
Dept. of Biomed., Electron. & Telecommun. Eng., Univ. Federico II of Naples, Naples, Italy
fYear :
2010
fDate :
25-30 July 2010
Firstpage :
1992
Lastpage :
1995
Abstract :
Information mining systems typically do not carry out image segmentation because a single algorithm could never perform well on the wide variety of sources and user applications encountered in practice. On the other hand, a large number of tools have been proposed in the literature that handle specific segmentation tasks very well. Dynamic segmentation is a possible solution, where the image is split recursively, in a hierarchical fashion, and different tools are used at each step to address specific segmentation tasks. In this work, the segmentation of a high-resolution test image is used as a running example and as a proof of concept of the potential of this approach.
Keywords :
data mining; image classification; image segmentation; image texture; dynamic segmentation; image classification; image information mining; image segmentation; texture segmentation; Heuristic algorithms; Image resolution; Image segmentation; Markov processes; Remote sensing; Roads; Skeleton; Texture segmentation; classification; image information mining; road extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location :
Honolulu, HI
ISSN :
2153-6996
Print_ISBN :
978-1-4244-9565-8
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2010.5651199
Filename :
5651199
Link To Document :
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