Employing active contours and artificial neural networks in representing ultrasonic range data

Date
2008-08
Advisor
Instructor
Source Title
16th European Signal Processing Conference, 2008
Print ISSN
Electronic ISSN
Publisher
IEEE
Volume
Issue
Pages
1 - 5
Language
English
Type
Conference Paper
Journal Title
Journal ISSN
Volume Title
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.

Course
Other identifiers
Book Title
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
Citation
Published Version (Please cite this version)