When a large number of documents, e.g. bank cheques, have to be authenticated in a limited time, the manual verification of, say the authors’ signatures, is often unrealistic. This led to the development of a wide range of automatic off-line signature verification systems. However, the value of such a system is rarely demonstrated by conducting a subjective test. We recently developed a novel o...

In this paper an on-line signature verification system, using vector quantization and Hidden Markov Model (VQ-HMM) is presented. After the signature acquisition, a Chebichef filter is used for noise reduction, and size and phase normalization is performed using Fourier transform. Each signature is segmented and mean velocity, acceleration and pressure are used as extracted features. K-means clu...

This paper presents a directed signature scheme with the property that the signature can be verified only with the help of signer or signature receiver. We also propose its applications to share verification of signatures and to threshold cryptosystems.

An aggregate signature scheme can aggregate n signatures on n distinct messages from n distinct signers into a single signature. , . Thus n verification equations can be reduced to one So the aggregate signature adapts to Mobile Ad hoc Network (MANET). In this paper, we propose an efficient IDbased aggregate signature scheme with constant pairing computations. Compared with the existing IDbased...

A new approach to off-line signature verification using non parametric Bayesian approach is discussed. Given sample(s) of Genuine signatures of an individual, the task of signature verification is a problem of classifying a questioned(test) signature as Genuine or Forgery(skilled). The verification problem is a two step approach (i)Enrollment: Genuine signature samples of an individual are prov...

Signature verification is a common task in forensic document analysis. It is one of determining whether a questioned signature matches known signature samples. From the viewpoint of automating the task it can be viewed as one that involves machine learning from a population of signatures. There are two types of learning to be accomplished. In the first, the training set consists of genuines and...

An on-line signature verification scheme based on linear prediction coding (LPC) cepstrum and neural networks is proposed. Cepstral coefficients derived from linear predictor coefficients of the writing trajectories are calculated as the features of the signatures. These coefficients are used as inputs to the neural networks. A number of single-output multilayer perceptrons (MLPs), as many as t...

Hand-written signature is widely used for authentication and identification of individual. Since the hand-written signature can be random, because of presence of various curves and features, techniques like character recognition cannot be applied for signature verification. In this paper we present an off-line signature verification system based on combination of features extracted such as glob...

Human signatures are widely used for biometric authentication. For automatic online signature verification, rather than storing an image of the completed signature, data are represented in the form of a time series of pen position and status information allowing the extraction of temporal-based features. For visualisation purposes, signature images need to be recreated from time-series data. In...

Chung, Huang, Lai and Chen proposed an ID-based signature scheme on the elliptic curve cryptosystem. Their scheme is secure but requires 60.12 1 for signature generation and 87.24 1 for signature verification. In this article, we propose an improvement of their signature scheme with three results: The improved scheme reduces about 50% and 33% of time complexity respectively for both signature g...