Use of characteristic views in image classification

C. Hung, Shisong Yang, C. Laymon
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引用次数: 11

Abstract

This paper addresses the problem of image texture classification. We present a novel texture feature called "characteristic view", which is directly extracted from a sample sub-image corresponding to each texture class. The K-views template method is proposed to classify the texture pixels based on these features. The characteristic view concept is based on the assumption that in an image taken from the nature scenes, a specific texture class in this image will frequently reveal the repetitions of some certain classes of features. Different "views" can be obtained for these features from different spatial locations. Experimental results show the effectiveness of the proposed approach compared with other methods.
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特征视图在图像分类中的应用
本文主要研究图像纹理分类问题。我们提出了一种新的纹理特征,称为“特征视图”,它是直接从每个纹理类对应的样本子图像中提取的。基于这些特征,提出了K-views模板方法对纹理像素进行分类。特征视图的概念是基于这样的假设,即在取自自然场景的图像中,该图像中的特定纹理类将经常显示某些特定类别的特征的重复。这些特征在不同的空间位置可以获得不同的“视图”。实验结果表明,该方法与其他方法相比是有效的。
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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