Relevance Feedback and Latent Semantic Index Based Cultural Relic Image Retrieval

摘要

In this paper we present a novel relevance feedback and latent semantic index based cultural relic image retrieval system. First, the optimum weights that can be used for iterative retrieval is computed , then a semantic image link network is constructed to store the semantic correlation information between images, which is obtained from memorized relevance feedbacks. Following image relevance feedback , Latent semantic indexing is applied to image retrieval, which helps saving in storage and estimating the hidden semantic relationship among images. To illustrate the potential of such an approach a prototype image retrieval system has been developed and Preliminary experimental results on a database containing about 2000 images demonstrate the effectiveness of the proposed model.