Abstract
In this paper we present an evaluation of six well established line segment distance functions within the scope of line segment matching. We show analytically, using synthetic data, the properties of the distance functions with respect to rotation, translation, and scaling. The evaluation points out the main characteristics of the distance functions. In addition, we demonstrate the practical relevance of line segment matching and introduce a new distance function.
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This paper uses the materials of the report submitted at the 9th Open German-Russian Workshop in Pattern Recognition and Image Understanding, held on Koblenz, December 1–5, 2014 (OGRW-9-2014).
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Stefan Wirtz obtained a diploma in Biomathematics (Dipl.-Math. (FH)) from the University of applied science RheinAhrCampus Remagen in 2008. He is now working for Motec GmbH in the sector of driver assistance development since 2012. Previously, he worked for the Institute of Computational Visualistics in the Working Group Active Vision (Prof. Paulus) at the University of KoblenzLandau. There he worked as PhD student in the project “Software Techniques for Object Recognition (STOR)” which is funded by the German Research Foundation (DFG). His scientific interests can be associated with the fields of Image Processing, Pattern Recognition and especial the handling of uncertain knowledge.
Dietrich Paulus obtained a Bachelor degree in Computer Science from University of Western Ontario, London, Canada, followed by a diploma (Dipl.-Inf.) in Computer Science and a PhD (Dr.-Ing.) from FriedrichAlexander University ErlangenNuremberg, Germany. He obtained his habilitation in Erlangen in 2001. Since 2001 he is at the institute for computational visualistics at the University Koblenz-Landau, Germany where he became a full professor in 2002. He is head of the Active Vision Group (AGAS). His primary interests are computer vision and robot vision.
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Wirtz, S., Paulus, D. Evaluation of established line segment distance functions. Pattern Recognit. Image Anal. 26, 354–359 (2016). https://doi.org/10.1134/S1054661816020267
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DOI: https://doi.org/10.1134/S1054661816020267