NUI Maynooth

NUI Maynooth ePrints and eTheses Archive

NUIM Library

Data Fusion for Topographic Object Classification

Keyes, L. and Winstanley, Adam C. (2001) Data Fusion for Topographic Object Classification. Proceedings IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion Over Urban Areas . pp. 275-279.

[img]PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
76Kb

Abstract

This paper presents research conducted into the automatic recognition of features and objects on topographic maps (for example, buildings, roads, land parcels etc.) using a selection of shape description methods developed mostly in the field of computer vision. In particular the work here focuses on the proposal and evaluation of fusion techniques (at the decision level of representation) for the classification of topographic data. A set of Ordnance Survey large-scale digital data (1:1250 and 1:2500) was used to evaluate the classification performance of the shape recognition methods used. Each technique proved partially successful in distinguishing classes of objects, however, no one technique provided a general solution to the problem. Further outlined experiments combine these techniques, using a data fusion methodology, on the real-world problem of checking and assigning feature codes in large-scale Ordnance Survey digital data.

Subjects:Science & Engineering > Computer Science
ID Code:67
Deposited By:Dr. Adam Winstanley
Deposited On:17 Dec 2002
Journal or Publication Title:Proceedings IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion Over Urban Areas
Publisher:IEEE
Refereed:Yes

Repository Staff Only: item control page