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Inertia tensor as a way of feature vector definition for one-dimensional signatures

机译:惯性张量作为一维签名的特征向量定义方法

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Signature is a simple representation of an object or a process in the form of a mathematical function, a feature vector, a geometric shape, or others, intended to uniquely capture the significant characteristics of an object or a process at a certain state. Often, signature is used alone as a feature vector. But in many applications signature to feature space transformation can be done to reveal specific important features of signature itself, e.g. shape or statistical properties, and therefore significantly reduce the number of features. Such transformation can be done in number of ways, e.g. using wavelet or statistical analysis. In this paper we propose a novel technique of revealing different shape and statistical properties of a signature by treating it as a discrete rigid body and computing its inertia tensor and mass center coordinates. We study two basic cases of different mass distribution. We demonstrate the use of this method of surface analysis of ceramic parts manufactured by layered manufacturing technique.
机译:签名是数学函数,特征向量,几何形状或其他形式的对象或过程的简单表示,旨在唯一地捕获特定状态下的对象或过程的重要特征。通常,签名单独用作特征向量。但是在许多应用中,可以进行签名到特征空间的转换以揭示签名本身的特定重要特征,例如形状或统计属性,因此大大减少了特征数量。这样的变换可以通过多种方式来完成,例如。使用小波或统计分析。在本文中,我们提出了一种新颖的技术,通过将签名视为离散的刚体并计算其惯性张量和质心坐标来揭示签名的不同形状和统计特性。我们研究了两种不同质量分布的基本情况。我们演示了这种通过分层制造技术制造的陶瓷零件的表面分析方法的使用。

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