DocumentCode
2900044
Title
A split-and-merge segmentation algorithm for line extraction in 2D range images
Author
Borges, G.A. ; Aldon, M.J.
Author_Institution
Dept. of Robotics, Univ. des Sci. et Tech. du Languedoc, Montpellier, France
Volume
1
fYear
2000
fDate
2000
Firstpage
441
Abstract
This paper presents a segmentation method for line extraction in 2D range images. It uses a prototype-based fuzzy clustering algorithm in a split-and-merge framework. The split-and-merge structure allows one to use the fuzzy clustering algorithm without any previous knowledge on the number of prototypes. This algorithm aims to be used in mobile robots navigation systems for dynamic map building. Simulation results show its good performance compared to some classical approaches
Keywords
computerised navigation; edge detection; feature extraction; fuzzy set theory; image segmentation; mobile robots; robot vision; 2D range images; feature extraction; fuzzy clustering; line extraction; mobile robots; navigation; split-and-merge segmentation; Clustering algorithms; Data mining; Image segmentation; Indoor environments; Iterative algorithms; Mobile robots; Navigation; Path planning; Prototypes; Robot kinematics;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location
Barcelona
ISSN
1051-4651
Print_ISBN
0-7695-0750-6
Type
conf
DOI
10.1109/ICPR.2000.905371
Filename
905371
Link To Document