图像检索技术研究进展

近年来，互联网上视觉数据呈现出爆炸式的增长，越来越多的研究工作围绕图像搜索或图像检索技术而展开.早期的搜索技术仅采用文本信息，忽视了视觉内容作为排序的线索，导致搜索文本和视觉内容不一致.基于内容的图像检索（CBIR）技术充分利用视觉内容识别相关图像，在近几年来获得了广泛关注.在图像检索中，最根本的问题是意图鸿沟和语义鸿沟，围绕该问题，近年涌现出大量的基于内容的图像检索的技术.本文主要对2003-2016年间提出的相关图像检索方法进行总结、分类和评估，并对未来的潜在研究方向进行讨论.

Recent advance in content-based image retrieval:A literature survey

The explosive increase and ubiquitous accessibility of visual data on the Web have led to the prosperity of research activity in image search or retrieval.With the ignorance of visual content as a ranking clue,methods with text search techniques for visual retrieval may suffer inconsistency between the text words and the visual content.Content-based image retrieval(CBIR),which makes use of the representation of visual content to identify relevant images,has attracted sustained attention in recent two decades.Such a problem is challenging due to the intention gap and the semantic gap problems.Numerous techniques have been developed for content-based image retrieval in the last decade.The purpose of this paper is to categorize and evaluate those algorithms proposed during the period of 2003 to 2016.We conclude with several promising directions for future research.