A Continuous Generalization of Linear Geographical Features by Morphing
ISBN 978-85-88783-11-9
Authors
1Jingzhong, L.; 2Tinghua, A.
1WUHAN UNIVERSITY Email: lilideyx@126.com
2WUHAN UNIVERSITY Email: tinghua_ai@163.net
Abstract
This paper presents a new method to continuously generalize linear geographical features like roads and rivers by shape morphing. In contrast to most conventional map generalization methods accepting one representation of a scale as input, the morphing based methods accept two different representations of the same entity at two different scales as input. This method is also known as the continuous generalization, because it can output the representation at any intermediate scale. The method addresses two key problems in geographical feature morphing process: characteristic points detection and feature correspondence. First, a robust characteristic points detection algorithm is developed based on constrained Delaunay triangulation model, by which the representation of coarser-scale is divided into several segments. Then an optimal problem is defined and solved to associate the characteristic points on the coarser-scale shape with the corresponding ones on the finer-scale shape. The algorithm decomposes the input shapes into several pairs of corresponding segments. Then the corresponding segments are interpolated in an as-rigid-as-possible plausible way(or using the intrinsic method). Thus interior distortions of the intermediate shapes could be avoided and the feature details on the input shapes could be well preserved. Experimental results show that the method can be used for continuous generalization and generate smooth, natural and visually pleasing linear geographical features morphing effects.
Keywords
morphing; feature correspondence; Continuous Generalization