TY - JOUR
T1 - Online Signature Recognition Based on Pseudo-Inked Signature Image Template
AU - Cho, Young One
AU - Jung, Jin Woo
N1 - Publisher Copyright:
© 2017 World Scientific Publishing Company.
PY - 2017/6/1
Y1 - 2017/6/1
N2 - As human-robot interaction is widely and increasingly used, automated user verification has become a necessary condition for system access. Signature recognition is one of the representative methods for user verification. In this paper, a novel method using Pseudo-Inked Signature for online signature recognition is proposed. Pseudo-Inked Signature consists of three types of information of pen pressure value, pen tilting angle, and pen theta angle during online signature writing. We propose a fusion method for three different types of information by mimicking the inked effect of real pen writing. Besides a style of penmanship, Pseudo-Inked Signature reflects the characteristics of handwriting behavior. Therefore, it can make different Pseudo-Inked Signature even though the original signature images from different users look very similar to each other. Similarly, it can also make more similar Pseudo-Inked Signatures even though the original signature images from the same user look somewhat different to each other. In addition, since only one gray-scale image is dealt with to represent the signature style of a person by Pseudo-Inked Signature image, it is efficient and very easy to handle. Finally, we tested user verification experiments using k-NN classifier. The experimental results show that Pseudo-Inked Signature is good enough for the real application.
AB - As human-robot interaction is widely and increasingly used, automated user verification has become a necessary condition for system access. Signature recognition is one of the representative methods for user verification. In this paper, a novel method using Pseudo-Inked Signature for online signature recognition is proposed. Pseudo-Inked Signature consists of three types of information of pen pressure value, pen tilting angle, and pen theta angle during online signature writing. We propose a fusion method for three different types of information by mimicking the inked effect of real pen writing. Besides a style of penmanship, Pseudo-Inked Signature reflects the characteristics of handwriting behavior. Therefore, it can make different Pseudo-Inked Signature even though the original signature images from different users look very similar to each other. Similarly, it can also make more similar Pseudo-Inked Signatures even though the original signature images from the same user look somewhat different to each other. In addition, since only one gray-scale image is dealt with to represent the signature style of a person by Pseudo-Inked Signature image, it is efficient and very easy to handle. Finally, we tested user verification experiments using k-NN classifier. The experimental results show that Pseudo-Inked Signature is good enough for the real application.
KW - online signature recognition
KW - personalized human-machine interaction
KW - Pseudo-Inked Signature
UR - http://www.scopus.com/inward/record.url?scp=85019678722&partnerID=8YFLogxK
U2 - 10.1142/S0219843617500165
DO - 10.1142/S0219843617500165
M3 - Article
AN - SCOPUS:85019678722
SN - 0219-8436
VL - 14
JO - International Journal of Humanoid Robotics
JF - International Journal of Humanoid Robotics
IS - 2
M1 - 1750016
ER -