Classifying image texture with statistical landscape features
Classifying image texture with statistical landscape features
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DOI：
10.1007/s10044-005-0014-6
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发表时间：
2006-02
影响因子：
3.9
通讯作者：
C. Xu;Y. Chen
中科院分区：
文献类型：
--
作者：
C. Xu;Y. Chen
本文提出利用图像函数图中的三维信息进行纹理描述。图像函数的图形是一个看起来像风景的皱巴巴的表面。为了刻画这一景观的纹理，使用了6条新的纹理特征曲线，该曲线基于图形和可变水平面形成的实体的几何和拓扑属性的统计。系统实验表明，在排除了一些非均匀图像、整个Brodatz纹理集以及Vistex纹理集合的情况下，所提出的统计景观特征在Brodatz纹理集的大子集上提供了非常低的错误率。
This paper proposes to use three-dimensional information derived from the graph of an image function for texture description. The graph of an image function is a rumpled surface appearing like a landscape. To characterize the texture through this landscape, six novel texture feature curves based on the statistics of the geometrical and topological properties of the solids shaped by the graph and a variable horizontal plane are used. The proposed statistical landscape features have been shown by systematic experiments to offer very low error rates on a large subset of the Brodatz texture album having excluded some nonhomogeneous images, the entire Brodatz texture set, as well as the VisTex texture collection.