DocumentCode :
1743055
Title :
Two-step classification based on scale space
Author :
Tang, Ming ; Xiao, Jing ; Ma, SongDe
Author_Institution :
Nat. Lab. of Pattern Recognition, Beijing, China
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
899
Abstract :
A new two-step classification scheme based on nonparametric estimation of density function and scale-space filtering is presented. This scheme is able to combine traditional supervised classification techniques with clustering. After nonparametric estimation of the underlying density function, this scheme utilizes scale-space filtering and a novel classification algorithm to extract the intrinsic basic structure of the data. Then, depending on applications, one of the traditional clustering or classification techniques may be employed to obtain a final high level data structure
Keywords :
data structures; filtering theory; pattern classification; clustering; data structure; density function; nonparametric estimation; scale space; scale-space filtering; Classification algorithms; Clustering algorithms; Clustering methods; Data mining; Data structures; Density functional theory; Filtering; Histograms; Laboratories; Noise robustness;
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.2000.906219
Filename :
906219
Link To Document :
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