  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.
