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Evaluation of different contour extraction approaches in the context of contour based image registration

: Brüstle, Stefan


Doucette, Peter J. (Ed.) ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Geospatial Informatics X : 27 April-8 May 2020, online only, United States
Bellingham, WA: SPIE, 2020 (Proceedings of SPIE 11398)
ISBN: 978-1-5106-3573-9
ISBN: 978-1-5106-3574-6
Paper 1139804, 8 pp.
Conference "Geospatial Informatics" <10, 2020, Online>
Conference Paper
Fraunhofer IOSB ()
georegistration; geolocation; matching; contour extraction; registration; segmentation; classification; polyline extraction

In recent years, imagery from airborne sensors has become available at low costs, due to the advent of affordable drone systems. Such imagery can be used for addressing many different tasks in various fields of application. While the imagery itself bears all of the information required for some tasks, other tasks require the imagery to be georeferenced satisfying certain accuracy requirements. If the latter is not the case when performing such tasks, registering the imagery to reference images that come with a satisfying georeference allows us to transfer this georeference to the imagery. Many registration approaches described in literature require an image and the reference to be of sufficiently similar appearance, in order to work properly. To address registration problems in more unsimilar cases, we have been developing a registration method based on contour matching. In a nutshell, this method comprises two main steps, namely contour point extraction from both the image and the reference and matching them. Towards the optimization of the overall performance of our registration method, we strive to improve the performance of each step individually, by both implementing new algorithms and fine-tuning relevant parameters. The scope of this work is the implementation of a novel contour point extraction algorithm to improve step one of our method, as well as its evaluation in the context of our registration method. Line shaped objects exceeding a certain length, such as e.g. road networks, are likely to be present both in the image and the reference, despite their possible appearance disimilarity. The novel contour point extraction algorithm capitalizes on this by focusing on the extraction of contour points representing such line shaped objects.