DocumentCode
1742853
Title
A constrained clustering algorithm for shape analysis with multiple features
Author
Marques, Jorge S. ; Abrantes, Arnaldo J.
Author_Institution
Inst. de Sistemas e Robotica, Inst. Superior Tecnico, Lisbon, Portugal
Volume
1
fYear
2000
fDate
2000
Firstpage
916
Abstract
This paper extends a class of constrained clustering methods for shape estimation by using the concept of extended features. The extended features consist of edge points and associated image properties, e.g., gradient, texture and color. Experimental results show that the use of extended features improves the performance of the algorithm in the presence of cluttered background
Keywords
edge detection; feature extraction; image colour analysis; image texture; constrained clustering; edge points; feature extraction; image color; image gradient; image texture; shape estimation; Active contours; Algorithm design and analysis; Clustering algorithms; Clustering methods; Data mining; Feature extraction; Image edge detection; Robustness; Sensor fusion; Shape;
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.2000.905586
Filename
905586
Link To Document