Narrowing Semantic Gap in Content-based Image Retrieval

Abstract

Due to the low-level image features it utilizes, the semantic gap problem is hard to bridge and performance of CBIR systems is still far away from users' expectation. Image annotation, region-based image retrieval and relevance feedback are three main approaches for narrowing the "semantic gap". In this paper, recent development in these fields are reviewed and some future directions are proposed in the end.