University of Bremen
Centre for Computing Technologies (TZI)
Am Fallturm 1, D-28359 Bremen
In the GIS domain we are often faced with a great amount of shape-related data. Therefore, it is a challenging task to find concise description approaches which support the efficient retrieval of specific objects. In order to address this demand we apply a method that has recently been introduced in the context of shape-based image retrieval of two-dimensional silhouettes, namely the scope histogram. Scope histograms pertain to the group of qualitative shape descriptions as they characterise a shape by the general configuration of its parts. In particular, scope histograms allow the comparison of two shapes with constant time complexity. Despite of its low complexity, the approach achieves promising retrieval results. However, up to now the definition of scope histograms is limited to closed polygons.
In this paper we investigate the application of scope histograms to the GIS domain. Since the contour of silhouettes is always closed, a restriction to closed polygons is no limitation in that domain. By contrast, it frequently is when dealing with GIS data. In this domain, we are rather often faced with open polygons; think for example of courses of rivers, borders, and coastlines. Therefore, we modify the original definition of scope histograms in order to be able to handle arbitrary polygons. Although our new definition leads to a more compact description than the original one, retrieval results are even improved by this modification.
Schuldt, A., Gottfried, B., and Herzog, O. (2006). A Compact Shape Representation for Linear Geographical Objects: The Scope Histogram. In Nittel, S. and de By, R. A. (eds.): 14th ACM International Symposium on Advances in Geographic Information Systems (ACM GIS 2006). Arlington, VA, USA, November 10-11, 2006. ACM Press, pp. 51-58.
© ACM, 2006. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM GIS 2006, Arlington, VA, USA, November 10-11