Off-line signature verification by the tracking of feature and stroke positions

✍ Scribed by B. Fang; C.H. Leung; Y.Y. Tang; K.W. Tse; P.C.K. Kwok; Y.K. Wong

• Publisher: Elsevier Science
• Year: 2003
• Tongue: English
• Weight: 219 KB
• Volume: 36
• Category: Article
• ISSN: 0031-3203
• DOI: 10.1016/s0031-3203(02)00061-4

✦ Synopsis

There are inevitable variations in the signature patterns written by the same person. The variations can occur in the shape or in the relative positions of the characteristic features. In this paper, two methods are proposed to track the variations. Given the set of training signature samples, the ÿrst method measures the positional variations of the one-dimensional projection proÿles of the signature patterns; and the second method determines the variations in relative stroke positions in the two-dimension signature patterns. The statistics on these variations are determined from the training set. Given a signature to be veriÿed, the positional displacements are determined and the authenticity is decided based on the statistics of the training samples. For the purpose of comparison, two existing methods proposed by other researchers were implemented and tested on the same database. Furthermore, two volunteers were recruited to perform the same veriÿcation task. Results show that the proposed system compares favorably with other methods and outperforms the volunteers.