使用对象、背景和条件搜索网络图像

Jiemi Zhang, Chenxia Wu, Deng Cai
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引用次数: 0

摘要

近十年来,随着网络图像量的快速增长,基于内容的图像检索(CBIR)作为一种有效的图像管理工具引起了人们的广泛关注。现有的CBIR系统大多关注图像中的物体,而忽略了条件(昼/夜、晴/雨等)和背景,这两者都非常有助于满足用户的信息需求。为了克服这一缺点,本文提出了一种基于新的查询公式的CBIR系统,该系统考虑了三个方面:对象、背景和条件。具体来说,我们设计了一个用户友好的界面来帮助用户制定查询。该界面允许用户给出每个对象在背景中的百分比、相对位置和大小。此外,提出了一种相应的有效排序方法,以返回期望的搜索结果。实验结果表明,与现有的搜索系统相比,我们提出的系统在搜索性能和用户体验上都有很大的提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Search web images using objects, backgrounds and conditions
As the volumes of web images have grown rapidly in the last decade, Content-Based Image Retrieval (CBIR) has attracted substantial interests as an effective tool to manage the images. Most existing CBIR systems focus on the object in the image, while ignoring the conditions (day/night, sunny/rain, etc) and the backgrounds, both of which are very helpful to meet the user's information need. To overcome this shortcoming, in this paper, we present a novel CBIR system depending on a novel query formulation considering three aspects: Object, Background and Condition. Specifically, we design a user-friendly interface to help the user formulate a query. The interface can allow the user to give the percentage, relative position and size of each object in the background. Moreover, a corresponding effective ranking method is proposed to return the desirable search results. Experimental results demonstrate that our proposed system improves the searching performance and the user experience compared with the existing searching systems.
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