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J4  2011, Vol. 45 Issue (2): 259-266    DOI: 10.3785/j.issn.1008-973X.2011.02.011
Bundling features with multiple segmentations for
object-based image retrieval
WANG Jin-de, SHOU Li-dan, LI Xiao-yan, CHEN Gang
College of Computer Science & Technology, Zhejiang University, Hangzhou 310027, China
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In the area of objectbased image retrieval, the traditional visual words (VW) based methods neglected the spatial relationship among local features, resulting in the low accuracy. To overcome this problem, a novel method of bundling features with multiple segmentations was proposed. In our method, images were multiple segmented, and all segmentations were described by SIFT features fallen inside the area to generate bundling features. The bundling features were matched based on the VW vocabulary. An improved similarity metric was presented to measure the similarity between matched bundling features, and the degree of similarity was infused into the vector space model of VW method, to calculate the image similarity. Experiments show that the proposed method can exploit the space relationships among local features, and improve the retrieval accuracy greatly with no significant reduction in the efficiency.

Published: 17 March 2011
CLC:  TP 391.41  
Cite this article:

WANG Jin-de, SHOU Li-dan, LI Xiao-yan, CHEN Gang. Bundling features with multiple segmentations for
object-based image retrieval. J4, 2011, 45(2): 259-266.

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