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      • Faculty of Engineering
      • Department of Electrical and Electronics Engineering
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      Employing active contours and artificial neural networks in representing ultrasonic range data

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      Author
      Altun, Kerem
      Barshan, Billur
      Date
      2008-08
      Source Title
      16th European Signal Processing Conference, 2008
      Publisher
      IEEE
      Pages
      [1] - [5]
      Language
      English
      Type
      Conference Paper
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      Abstract
      Active snake contours and Kohonen's self-organizing feature maps (SOM) are considered for efficient representation and evaluation of the maps of an environment obtained with different ultrasonic arc map (UAM) processing techniques. The mapping results are compared with a reference map acquired with a very accurate laser system. Both approaches are convenient ways of representing and comparing the map points obtained with different techniques among themselves, as well as with an absolute reference. Snake curve fitting results in more accurate maps than SOM since it is more robust to outliers. The two methods are sufficiently general that they can be applied to discrete point maps acquired with other mapping techniques and other sensing modalities as well. copyright by EURASIP.
      Keywords
      Active contours
      Active snakes
      Discrete points
      Kohonen's Self-organizing Feature Maps
      Laser systems
      Mapping techniques
      Processing technique
      Reference map
      Sensing modalities
      Ultrasonic range
      Conformal mapping
      Curve fitting
      Self organizing maps
      Signal processing
      Permalink
      http://hdl.handle.net/11693/26783
      Published Version (Please cite this version)
      https://ieeexplore.ieee.org/abstract/document/7080422
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      • Department of Electrical and Electronics Engineering 3614
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