Data fusion for topographic object classification
Laura Keyes, Adam C. Winstanley · 2002
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.