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
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;
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7695-0750-6
DOI :
10.1109/ICPR.2000.905371
