Overview of content-based image retrieval with high-level semantics

Semantic gap that between the visual features and human semantics has become a bottleneck of content-based image retrieval. The need for improving the retrieval accuracy of image retrieval systems and narrowing down the semantic gap is high in view of the fast growing need of image retrieval. In this paper, we first introduce the image semantic description methods, then we discuss the main technologies for reducing the semantic gap, namely, object-ontology, machine learning, relevance feedback. Applications of above-mentioned technologies in various areas are also introduced. Finally, some future research directions and problems of image retrieval are presented.