This paper presents a novel approach to the digital signing of electronic
documents through the use of a camera-based interaction system, single-finger
tracking for sign recognition, and multi commands executing hand gestures. The
proposed solution, referred to as "Air Signature," involves writing the
signature in front of the camera, rather than relying on traditional methods
such as mouse drawing or physically signing on paper and showing it to a web
camera. The goal is to develop a state-of-the-art method for detecting and
tracking gestures and objects in real-time. The proposed methods include
applying existing gesture recognition and object tracking systems, improving
accuracy through smoothing and line drawing, and maintaining continuity during
fast finger movements. An evaluation of the fingertip detection, sketching, and
overall signing process is performed to assess the effectiveness of the
proposed solution. The secondary objective of this research is to develop a
model that can effectively recognize the unique signature of a user. This type
of signature can be verified by neural cores that analyze the movement, speed,
and stroke pixels of the signing in real time. The neural cores use machine
learning algorithms to match air signatures to the individual's stored
signatures, providing a secure and efficient method of verification. Our
proposed System does not require sensors or any hardware other than the camera.

该论文提出了一种新颖的数字签名方法，使用基于相机的交互系统、单指跟踪将手势识别和多命令执行结合在一起。该方法称为 “空中签名”，旨在开发一种实时检测和跟踪手势和物体的最先进方法。还提出了用于平滑处理和线条绘制的现有手势识别和物体跟踪系统，并在快速手指运动期间保持连续性。此外，还通过评估指尖检测、草图绘制和整个签名过程的效果来验证所提出的解决方案的有效性，并开发了一套能够有效识别用户独特签名的模型，利用神经核心实时分析签名的运动、速度和笔画像素，并使用机器学习算法将空中签名与个人存储的签名进行匹配，提供了一种安全高效的验证方法。该系统不需要传感器或相机以外的任何硬件。