Institute of Automation, Key Laboratory of UWB & THz of Shandong Academy of Sciences, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China.
Sci Rep. 2022 Oct 24;12(1):17806. doi: 10.1038/s41598-022-21770-8.
In this work, a method of pretreating THz absorption curve is proposed, which leads to minimal range in absorption, reserving necessary undulation of curve for identification by convolutional neural network. The kernel thought of proposed method is about confining the undulation of curve with a pair of narrow parallel lines and solving their optimal position by consecutively rotation of normalized curve at two fixed points. A fast algorithm is further proposed based on features of convex hull, whose procedure is described in detail. The algorithm involves definition of some important point sets, calculating and comparing slopes and determining best choice out of 4 potential rotations. The rationality of searching critical point is illustrated in a geometric way. Additionally, the adaption of the method is discussed and real examples are given to show the capacity of method to extract nonlinear information of a curve. The study suggests that methods regarding computer graphics also contributes to feature extraction with respect to THz curve and pattern recognition.
在这项工作中，提出了一种太赫兹吸收曲线预处理方法，该方法使吸收的范围最小化，为卷积神经网络的识别保留必要的曲线波动。该方法的核心思想是用一对窄平行线约束曲线的波动，并通过在两个固定点处连续旋转归一化曲线来求解其最佳位置。进一步提出了一种基于凸包特征的快速算法，详细描述了其过程。该算法涉及一些重要点集的定义、斜率的计算和比较，并从 4 个潜在旋转中确定最佳选择。通过几何方法说明了搜索临界点的合理性。此外，还讨论了该方法的适应性，并给出了实际示例，以显示该方法提取曲线非线性信息的能力。该研究表明，计算机图形学方法也有助于太赫兹曲线和模式识别中的特征提取。
