Shape Similarity Measure Based on Correspondence of Visual Parts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Maintaining knowledge about temporal intervals
Communications of the ACM
Qualitative Spatial Representation and Reasoning: An Overview
Fundamenta Informaticae - Qualitative Spatial Reasoning
Towards the visualisation of shape features: the scope histogram
KI'06 Proceedings of the 29th annual German conference on Artificial intelligence
Characterising meanders qualitatively
GIScience'06 Proceedings of the 4th international conference on Geographic Information Science
Retrieving shapes efficiently by a qualitative shape descriptor: the scope histogram
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
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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.