Robust approach for textured image clustering

A. Ennouni, M. A. Sabri, S. Senhaji, A. Aarab
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引用次数: 4

Abstract

Texture is considered as a big issue in image clustering and influence directly on the processing results. So, the idea here is to propose a new approach for image segmentation based on texture-isolation to reduce their effects and to identify easily the different clusters in an image. In this aim, we propose to use first a pre-processing method based on multiscale approach to separate a textured image into texture and geometrical components, applying a filtering process to smooth boundaries, at the end the geometrical component will be used in the classification stage. Several multiscale models, filtering algorithm and classification approaches have been tested on this paper. Simulation results with a comparison study show the good quality of the proposed approach.
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纹理图像聚类的鲁棒方法
纹理是图像聚类中的一个重要问题,它直接影响图像聚类处理的结果。因此,本文提出了一种基于纹理隔离的图像分割方法,以减少纹理隔离对图像分割的影响,并方便地识别图像中的不同聚类。为此,我们建议首先使用基于多尺度方法的预处理方法将纹理图像分离为纹理和几何分量,并对边界进行滤波处理,最后将几何分量用于分类阶段。本文对几种多尺度模型、滤波算法和分类方法进行了测试。仿真结果和对比研究表明了该方法的良好性能。
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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