DESIGN OF DIGITAL SIGNATURE VERIFICATION ALGORITHM USING RELATIVE SLOPE METHOD

2014 ◽  
Vol 03 (08) ◽  
pp. 384-388
Author(s):  
P.N .Ganorkar .
Author(s):  
Luan L. Lee ◽  
Miguel G. Lizarraga ◽  
Natanael R. Gomes ◽  
Alessandro L. Koerich

This paper describes a prototype for Brazilian bankcheck recognition. The description is divided into three topics: bankcheck information extraction, digit amount recognition and signature verification. In bankcheck information extraction, our algorithms provide signature and digit amount images free of background patterns and bankcheck printed information. In digit amount recognition, we dealt with the digit amount segmentation and implementation of a complete numeral character recognition system involving image processing, feature extraction and neural classification. In signature verification, we designed and implemented a static signature verification system suitable for banking and commercial applications. Our signature verification algorithm is capable of detecting both simple, random and skilled forgeries. The proposed automatic bankcheck recognition prototype was intensively tested by real bankcheck data as well as simulated data providing the following performance results: for skilled forgeries, 4.7% equal error rate; for random forgeries, zero Type I error and 7.3% Type II error; for bankcheck numerals, 92.7% correct recognition rate.


2014 ◽  
Vol 513-517 ◽  
pp. 2016-2019
Author(s):  
Xiao Feng Wang

This paper describes the concept of XML digital signatures, analyzes the digital signature and the signature verification process, describes the W3C digital signature specification, and studies how to ensure data security in network exam in C #.NET environment. Experiments show that: XML digital signature in network test system ensures the integrity of network data transmission, the identity of verifiability and non-repudiation.


Author(s):  
JULIO CESAR MARTÍNEZ ROMO ◽  
ROGELIO ALCÁNTARA SILVA

It is well known that the approach of functions of time to represent the dynamic and static characteristics of signatures usually outperforms the approaches based on parameters; in addition to this result, we propose here that the model or prototype function of the discriminant features of the signatures should be created considering the signature verification problem as a bi-objective optimization problem in which the false acceptance and false rejection rates are minimized simultaneously; to accomplish these goals, a discrete space of solutions is searched by a genetic algorithm, and a continuous space of solutions is searched by a modified gradient method, both spaces containing candidate prototype functions and the one that best meets some optimization criteria is first chosen as the optimal prototype function and then improved. Given that creating the prototype functions of features is just one of the earlier steps of a signature verification system, we also propose here a scheme of signature verification algorithm with intelligent classification. Our approach was tested in the context of random and highly skilled forgeries, with error rates below 0.1% over 7,300 verifications. Our database consisted of 1,762 exemplars, containing genuine signatures and skilled forgeries from 36 persons. Comparison to other methods of making prototype functions of features is shown.


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