Overview of content-based image retrieval with high-level semantics
2010Vol. 41, pp. V6–312
Citations Over Time
Abstract
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.
Related Papers
- → A novel log-based relevance feedback technique in content-based image retrieval(2004)95 cited
- → A REVIEW ON CONTENT BASED IMAGE RETRIEVAL(2017)7 cited
- → Image Retrieval using Bipartite Reiterative Algorithm(2015)
- Research on semantic annotation to cultural relic images based on relevance feedback(2008)