基于内容索引和检索的图像纹理分形分析

André G. R. Balan, A. Traina, C. Traina, P. M. A. Marques
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引用次数: 39

摘要

本文提出了将分形分析作为区分医学图像纹理分割区域的一种方法。我们表明,使用分形可以提高传统图像特征的表示水平,从而在回答使用方差加权曼哈顿距离的图像的相似性查询时具有较高的精度。计算分形测量值的成本与图像大小呈线性关系,这使得它们成为大型图像集的合适选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fractal analysis of image textures for indexing and retrieval by content
This paper proposes the use of fractal analysis as a means to discriminate textured segmented regions of medical images. We show that the use of the fractals can boost the representation level of traditional image features allowing high rates of precision when answering similarity queries over images employing a variance weighted Manhattan distance. The cost to compute the fractal measurements is linear on the image size, what makes their use a suitable choice for large sets of images.
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