DocumentCode :
2853834
Title :
Object Based Clustering Using Hybrid Algorithms
Author :
Razak, Nor Hafizah Abd ; Manshor, Noridayu ; Rajeswari, Mandava ; Ramachandram, Dhanesh
Author_Institution :
Comput. Vision Res. Group, Univ. Sains Malaysia, Penang
fYear :
2008
fDate :
26-28 Aug. 2008
Firstpage :
12
Lastpage :
17
Abstract :
This paper presents a hybrid algorithm for object based clustering. The algorithm is designed based on hybrid of hierarchical and k-means clustering algorithm. For this work, we used dataset consist of natural imagery collected from PASCAL database 2006 collection and Google images. A collection of low level features image is used to validate the performance of our approach. Experimental results show that hybrid algorithm produced higher accuracy compared to k-means and hierarchical algorithm by up to 25%.
Keywords :
image recognition; pattern clustering; visual databases; Google images; PASCAL database 2006 collection; hybrid algorithms; k-means clustering algorithm; natural imagery collected; object based clustering; Algorithm design and analysis; Clustering algorithms; Computer graphics; Computer vision; Data mining; Feature extraction; Humans; Partitioning algorithms; Shape; Visualization; Hierarchical; K-means; hybrid algorithm; object based clustering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Graphics, Imaging and Visualisation, 2008. CGIV '08. Fifth International Conference on
Conference_Location :
Penang
Print_ISBN :
978-0-7695-3359-9
Type :
conf
DOI :
10.1109/CGIV.2008.53
Filename :
4626977
Link To Document :
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