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| Image Retrieval with Spatial Context Weighting Based Vocabulary Tree |
| ZHU Dao-Guang,GUO Zhi-Gang,ZHAO Yong-Wei |
| Institute of Information System Engineering,Information Engineering University,Zhengzhou 450002 |
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Abstract Vocabulary tree based Bag-of-Words (BoW) representation becomes popular for image retrieval recently. Aiming at the absence of spatial context information in conventional vocabulary tree approaches,an image retrieval approach using spatial context weighting based vocabulary tree is proposed. Within the framework of vocabulary tree,this approach firstly describes the spatial context information of SIFT features. Then,the matching scores between SIFT features are weighted based on spatial context similarity,and similarities between images are achieved. Finally,image retrieval results are obtained according to the ranking of similarities. The experimental results indicate that the retrieval performance is improved and the proposed approach applies to large scale databases.
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Received: 16 November 2012
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2013, Vol. 26 
