基于人工徒步和分形的纹理表示与分类

L. A. Soares, K. F. Côco, E. Salles, P. M. Ciarelli
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引用次数: 1

摘要

这项工作提出了一种新的方法,通过它们的最大值(或最小,如果使用图像的负极)和不同的强度边界来表示数字图像上的纹理,通过称为人工徒步者的人工生物来搜索纹理图像的最大值,并在这样做时代表图像的不同特征。该技术有两个主要参数可以调整,以强调图像的最大值和不同的频率边界。结果表明,它是一种非常灵活的表示纹理图像的不同成分的技术,既适用于自然图像,也适用于人工图像。在纹理分类方面,将人工徒步者技术与分形维数分析相结合,取得了优于以往人工智能体纹理分类的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Texture Representation and Classification with Artificial Hikers and Fractals
This work proposes a new method of representing textures on digital images through their maximum (or minimum if the negative of the image is used) and different intensity borders by means of artificial beings called artificial hikers that search for the maximum of a texture image and in doing so, represent the different characteristics of the image. The technique has two main parameters that can be adjusted in order to emphasize the greatest maximum of an image and different frequency borders. The results show that it is a very flexible technique on representing different components of a texture image, working on both natural and artificial images. For the classification of textures, the technique of artificial hikers was combined with fractal dimension analysis and it presented superior results compared to previous works dealing with texture classification with artificial agents.
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