The Integraton of Graph-Based Knowledge Discovery with Image Segmentation Hierarchies for Data Analysis, Data Mining and Knowledge Discovery

Author

Tilton, James C. ; Cook, Diane J. ; Ketkar, Nikhil

Author_Institution

Code 606.3, NASA Goddard Space Flight Center, Greenbelt, MD

Volume

3

fYear

2008

fDate

7-11 July 2008

Abstract

Currently available pixel-based image analysis techniques do not effectively extract the information content from the increasingly available high spatial resolution remotely sensed imagery data. We are exploring an approach to object-based image analysis in which hierarchical image segmentations provided by the Recursive Hierarchical Segmentation (RHSEG) software are analyzed by the Subdue graph-based knowledge-discovery system. In this paper we discuss our initial approach to representing the RHSEG-produced hierarchical image segmentations in a graphical form understandable by Subdue, and discuss results from real and simulated data.

Keywords

data mining; geophysical signal processing; image segmentation; remote sensing; Recursive Hierarchical Segmentation software; Subdue; data mining; graph-based knowledge discovery; high spatial resolution remotely sensed imagery; image segmentation; object-based image analysis; pixel-based image analysis; Clustering algorithms; Computer science; Data analysis; Data mining; Image analysis; Image segmentation; NASA; Pattern analysis; Pixel; Spatial resolution; Object-based image analysis; graph-based analysis; hierarchical image segmentation; knowledge discovery;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International

Conference_Location

Boston, MA

Print_ISBN

978-1-4244-2807-6

Electronic_ISBN

978-1-4244-2808-3

Type

conf

DOI

10.1109/IGARSS.2008.4779391

Filename

4779391