Content-Based Retrieval of Cultural Relic Images in Digital Museum

摘要

With the popularization of digital museum, effective retrieval in huge image databases of special domain has attracted much research attention. As an effect approach, corresponding semantic information is adopted in many retrieval systems. However, most cultural relic retrieval systems only supply the explicit use of semantic information. It requires the user to be professional in this domain. In this paper, we propose a novel relevance feedback method which combines semantic annotation to visual feature implicitly. With this method, the user can unknowingly use professional semantic information to retrieve images. We also do some improvement in feature extraction and similarity measurement methods to fit the retrieval basis of unprofessional user better. The experiment results show that our approach is effective and efficient.