Abstract:
A signature is an ability learned by humans from an elementary age. The skill to generate one's own exclusive signature along with imitating another writer's signature is...Show MoreMetadata
Abstract:
A signature is an ability learned by humans from an elementary age. The skill to generate one's own exclusive signature along with imitating another writer's signature is a challenging and complex task. In real time scenarios like E-Commerce and M-Commerce payments, user verification based on online signatures constrain the verification framework needs to be trained extensively with huge samples, which unfeasible to obtain. Hence, as a solution, in this paper, we propose a first its of kind of attempt in which an intelligent framework tries to learn the online signatures of a writer using Deep Generative Adversarial Networks (DGANs). Thorough experimental analysis on three widely used datasets MCYT-100, SVC, SUSIG confirms the supremacy of the method and boost confidence in real time deployment of our framework in data centric applications like offline signature verification, forged document detection, etc.
Date of Conference: 07-11 January 2020
Date Added to IEEE Xplore: 09 March 2020
ISBN Information: