Image classification using subgraph histogram representation
Author
Özdemir, Bahadır
Aksoy, Selim
Date
2010Source Title
2010 20th International Conference on Pattern Recognition
Print ISSN
1051-4651
Publisher
IEEE
Pages
1112 - 1115
Language
English
Type
Conference PaperItem Usage Stats
124
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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.
Keywords
Bag of wordsData 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