Semi-automatic BPT for Image Retrieval

Shirin Ghanbari, J. Woods, S. Lucas
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引用次数: 1

Abstract

This paper presents a novel semi-automatic tool for content retrieval. A multi-dimension Binary Partition Tree (BPT) is generated to perform object based image retrieval. The tree is colour based but has the advantage of incorporating spatial frequency to form semantically meaningful tree nodes. For retrieval, a node of the query image is matched against the nodes of the BPT of the database image. These are matched according to a combination of colour histograms, texture features and edge histograms. This semi-automatic tool allows users to have more freedom in their choice of query. The paper illustrates how the use of multi-dimensional information can significantly enhance content retrieval results for natural images.
半自动BPT图像检索
提出了一种新的半自动内容检索工具。生成了一个多维二叉分割树(BPT)来执行基于对象的图像检索。该树是基于颜色的,但具有结合空间频率形成语义上有意义的树节点的优势。对于检索,查询图像的节点与数据库图像的BPT的节点进行匹配。根据颜色直方图、纹理特征和边缘直方图的组合进行匹配。这个半自动工具允许用户在选择查询时有更多的自由。本文说明了如何使用多维信息可以显著提高自然图像的内容检索结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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