New In-Air Signature Datasets

• Main Authors: Alobaidi, AbdulAzeez R., Dhieb, Thameur, Nuimi, Zeina N., Hamdani, Tarek M., Wali, Ali, Alimi, Adel M.
• Format: Conference Proceeding
• Language: English
• Subjects: Biometrics (access control); Cameras; forgery; genuine; Glass; Handwriting recognition; identification; in-air signature dataset; Portable computers; Robustness; verification; Writing
• ISSN: 2768-0940
• DOI: 10.1109/ISNCC58260.2023.10323719

Compared to traditional biometric systems, in-air signatures are considered more robust and secure than classical pen paper. A few datasets capturing in-air signatures have been introduced, utilizing various devices such as the Leap Motion and the Microsoft Kinect sensor camera. However, these devices are not exempt from shortcomings and exhibit certain limitations. The expenses associated with their implementation and the requirement for technical proficiency in operating them present notable challenges for in-air signature analysis. Additionally, users may encounter difficulties in adapting their finger movements to fit within the device's limited field of view, particularly if they lack familiarity with these devices. To address these concerns, this paper proposes the creation of three in-air signature datasets using solely the camera of a laptop or a smartphone, eliminating the need for any additional specialized equipment. Our datasets were collected in three ways. The first is the In-Air Signature dataset (IAS dataset) and the second is the In-Air Signature dataset using a transparent Glass Plate (IASGP dataset) while the third is the In-Air Signature dataset using Smart Phone (IASSP dataset). Forty volunteers participated in the construction of these datasets. Their ages ranged from 21 to 40 years. Each volunteer signs in the air five signatures and imitates five signatures of five other volunteers. Our in-air signatures datasets are publicly available and can be used for various research tasks like in-air signature verification and identification.