Off-line signature verification without requiring random forgeries for training

/in , , /by
Off-line signature verification without requiring random forgeries for training

Murshed, Nabeel A. and Bortolozzi, Flávio and Sabourin, Robert

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 1995

Abstract : This paper presents an Off-line Signature Verification System for the elimination of random forgeries. Compared with the proposed systems thus far, our system is trained with genuine signatures only. This eliminates many of the problems existent in the current systems. The proposed system is evaluated with a data base of 200 signatures.

You might also like
Revisiting learnable affines for batch norm in few-shot transfer learning
Quantitative identification of nonmuscle-invasive and muscle-invasive bladder carcinomas: a multiparametric MRI radiomics analysis
An end-to-end approach for recognition of modern and historical handwritten numeral strings
Spectral graph transformer networks for brain surface parcellation
Effective level set image segmentation with a kernel induced data term
A Strategy for Selecting Classes of Symbols from Classes of Graphemes in HMM-Based Handwritten Word Recognition
Mining graphs to discover new theorems in mathematics
Quantitative Identification of Nonmuscle-Invasive and Muscle-Invasive Bladder Carcinomas: A Multiparametric MRI Radiomics Analysis