采用特征滤波器来提取样本集中具有线性特征的点，同时生产样本点之间的相互关系；

A feature filter is presented to extract linear points and their relations from input samples.

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提出了一种由数据分析、特征滤波器、假设检验、融合决策等过程组成的隐藏攻击方法。

In the end, the paper proposed a way of hiding attack technique composed by data analysis, characteristic filter, hypothesis inspection and syncretism decision-making.

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所提供的特征滤波器与传统的滤波器相比，可以有效挑选出数量更少、分类性能更优的纹理特征。

We can achieve better classification performance by the feature filters comparable to other traditional filter schemes while resulting in considerably smaller filters.

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