Intelligent Image Retrieval Using Neural Network

概要

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In content-based image retirieval(CBIR), the content of an image can be expressed in terms of different features such as color, texture, shape, or text annotations. Retrieval methods based on these features can be varied depending on how the feature values are combined. Many of the existing approaches assume linear relationships between different features, and also require users to assign weight to features for themselves. Other nonlinear approaches have mostly concentrated on indexing technique. While the linearly combining approach establishes the basis of CBIR, the usefulness of such systems is limited due to the lack of the capability to represent high-level concepts using lowlevel features and human perception subjectivity. In this paper, we introduce a Neural Network-based Image Retrieval(NNIR) system, a human-computer interaction approach to CBIR using the Radial Basis Function(RBF) network. The proposed approach allows the user to select an initial query image and incrementally search target images via relevance feedback. The experimental results show that the proposed approach has the superior retrieval performance over the existing linearly combining approach, the rank-based method, and the BackPropagation-based method.
社団法人電子情報通信学会の論文
2001-12-01