management and retrieval become urgent requirements to image users and managers. Content-based image retrieval (CBIR) is a good solution for this problem
and has attracted increasing attention from researchers all over the world recently. In this paper
we review the beginning and various applications of CBIR firstly
and then we introduce some key techniques and algorithms for CBIR
such as methods and principals for image feature selection and representation
feature-based similarity computation
semantic features and relevance feedback. CBIR inherits some automatic techniques from traditional computer vision. However
CBIR and computer vision are very different in essence. We put forward our views on both common and distinct characters between them in the concluding section. CBIR is distinguished by the ability of on-line learning through interactive with users. Future research directions are also be presented in this section
including relevance feedback
features fusion
database technique and hierarchical ordered descriptions about the semantic content of images.