Natural Scene Retrieval Based on Graph Semantic Similarity for Adaptive Scene Classification

Authors:
Nuraini Jamil;Sanggil Kang
Affiliations:
Department of Computer and Information Engineering, Inha University, Incheon, Korea 402-751;Department of Computer and Information Engineering, Inha University, Incheon, Korea 402-751
Venue:
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Year:
2009

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Abstract

In this paper, we introduce our method for image retrieval to access and measuring the similarity of natural scenes by using graph semantic similarity. The proposed method is motivated by continuing effort from our previous work in adaptive image classification based on semantic concepts and edge detection. The method will learn the image information by concept occurrence vector of semantic concepts such as water, grass, sky and foliage. We constructed the graph using this information and illustrate the similarity with connecting edges. The empirical results demonstrated promising performance in terms of accuracy.