Employing active contours and artificial neural networks in representing ultrasonic range data
Author
Altun, Kerem
Barshan, Billur
Date
2008-08Source Title
16th European Signal Processing Conference, 2008
Publisher
IEEE
Pages
[1] - [5]
Language
English
Type
Conference PaperItem Usage Stats
78
views
views
11
downloads
downloads
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 contoursActive 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