DocumentCode
457168
Title
A Clustering-based Algorithm for Extracting the Centerlines of 2D and 3D Objects
Author
Ferchichi, Seifeddine ; Wang, Shengrui
Author_Institution
Sherbrooke Univ., Que.
Volume
2
fYear
0
fDate
0-0 0
Firstpage
296
Lastpage
299
Abstract
This paper presents a new algorithm for extracting the centerlines of 2D and 3D objects, based on clustering. The algorithm computes the centerline from all points of the object in order to remain faithful to the structure of the shape. The idea is to cluster a data set constituted of the points composing the object and their relative distance transforms. The centerline is derived from the set of computed clusters. The proposed method is accurate and robust to noisy boundaries
Keywords
feature extraction; object detection; pattern clustering; transforms; 2D object; 3D object; centerlines extraction; clustering-based algorithm; distance transform; Biomedical imaging; Clustering algorithms; Computer vision; Data mining; Noise shaping; Object recognition; Robustness; Shape; Skeleton; Solid modeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location
Hong Kong
ISSN
1051-4651
Print_ISBN
0-7695-2521-0
Type
conf
DOI
10.1109/ICPR.2006.44
Filename
1699205
Link To Document