Image classification using subgraph histogram representation

Date
2010
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Source Title
2010 20th International Conference on Pattern Recognition
Print ISSN
1051-4651
Electronic ISSN
Publisher
IEEE
Volume
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Pages
1112 - 1115
Language
English
Type
Conference Paper
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Abstract

We describe an image representation that combines the representational power of graphs with the efficiency of the bag-of-words model. For each image in a data set, first, a graph is constructed from local patches of interest regions and their spatial arrangements. Then, each graph is represented with a histogram of subgraphs selected using a frequent subgraph mining algorithm in the whole data. Using the subgraphs as the visual words of the bag-of-words model and transforming of the graphs into a vector space using this model enables statistical classification of images using support vector machines. Experiments using images cut from a large satellite scene show the effectiveness of the proposed representation in classification of complex types of scenes into eight high-level semantic classes. © 2010 IEEE.

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Keywords
Bag of words, Data sets, Frequent subgraph mining, High level semantics, Image representations, Interest regions, Spatial arrangements, Statistical classification, Subgraphs, Visual word, Graphic methods, Pattern recognition, Support vector machines, Vector spaces, Statistical methods
Citation
Published Version (Please cite this version)