In order to tackle the problem of consistently integrating 2d vector data and a dTM, we presented an approach for the adaptation of 2d GIS road objects to airborne laser scanning (ALS) data using active contours (snak...
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In order to tackle the problem of consistently integrating 2d vector data and a dTM, we presented an approach for the adaptation of 2d GIS road objects to airborne laser scanning (ALS) data using active contours (snakes) in (Göpfert et al., 2011). In this paper the algorithm is modified for the integration of stereo images as an alternative data source for area-wide height information. For that reason, a new image energy is developed that exploits geometric and radiometric features derived from the image data. Afterwards, we compare the applicability of our method with respect to the ALS data and stereo images as input. In addition, a new approach is suggested that analyses the different energy terms of active contours after the optimisation process in order to automatically detect contour parts that did not reach a suitable position in the sensor data. This concept of an internal evaluation is able to guide the user during post processing. Experiments show that the snake approach with an image energy based on stereo images is generally able to adapt GIS road centrelines to the sensor data and thus to improve the quality of the 2d vector data. However, the comparison to the results for ALS datademonstrates that the algorithm perform slightly worse for image data in the high precision level.
We study the watermarking of 2d vector data and introduce a framework which preserves topological properties of the input. Our framework is based on so-called maximum perturbation regions (MPR) of the input vertices, ...
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ISBN:
(纸本)9781424474936
We study the watermarking of 2d vector data and introduce a framework which preserves topological properties of the input. Our framework is based on so-called maximum perturbation regions (MPR) of the input vertices, which is a concept similar to the just-noticeable-difference constraint. The MPRs are computed by means of the Voronoi diagram of the input and allow us to avoid (self-)intersections of input objects that might result from the embedding of the watermark. We demonstrate and analyze the applicability of this new framework by coupling it with a well-known approach to watermarking that is based on Fourier descriptors. However, our framework is general enough such that any robust scheme for the watermarking of vectordata can be applied.
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