笔迹
加速度
计算机科学
特征(语言学)
模式识别(心理学)
人工智能
线性判别分析
傅里叶变换
追踪
签名(拓扑)
频域
语音识别
特征提取
时域
计算机视觉
数学
物理
数学分析
语言学
哲学
几何学
经典力学
操作系统
作者
Yang Yang,Xingzhou Han,Dashan Qin
标识
DOI:10.1111/1556-4029.15386
摘要
The utilization of handwritten electronic signatures has expanded in various application scenarios, leading to an increased demand for identification. Unlike handwriting signatures, handwritten electronic signatures offer the advantage of extracting dynamic feature data, including writing pressure, velocity, and acceleration. In this study, the Fourier transform was employed to extract 18 characteristics from the time domain and frequency domain of writing pressure, velocity, and acceleration. The experimental findings revealed distinguishable differences between genuine signatures and random forgeries in writing pressure. However, no statistically significant differences were observed in writing velocity and writing acceleration. Moreover, significant differences were detected in most characteristics when comparing genuine signatures with freehand imitation forgeries and tracing imitation forgeries. The canonical discriminant analysis was performed between the genuine and Non-genuine signatures; the cross-validation estimated the discriminating power of these characteristics with a satisfactory result. The study proposed a new approach to analyzing handwritten electronic signatures using time-domain and frequency-domain characteristics and demonstrated its effectiveness in the examination.
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