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Signature recognition

About: Signature recognition is a research topic. Over the lifetime, 2138 publications have been published within this topic receiving 37605 citations.


Papers
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Proceedings ArticleDOI
01 Feb 2017
TL;DR: This paper proposed and implemented an innovative approach based on upper and lower envelope and Eigen values techniques that gives better performance than already established offline signature recognition methods.
Abstract: Automatic signature recognition is most active area of research with number of applications such as financial, official work, bank cheque, business etc. To obtain maximum possible security from fake signature there is emergent need for a signature recognition, which can assure good results and gives better performance than already established offline signature recognition methods. In this paper, we proposed and implemented an innovative approach based on upper and lower envelope and Eigen values techniques. Envelope represents the shape of the signature. The feature set consists of features such as large and small Eigen values computed from upper envelope and lower envelope and its union values. Both the envelopes are fused by performing union operation and their covariance is computed. The difference and ratios of high and low points of both the envelopes are computed. Lastly average values of both the envelopes are obtained. These features set are coupled with support vector machine classifier that lead to 98.5 % of accuracy.

14 citations

Journal ArticleDOI
TL;DR: The maximum a posteriori (MAP) estimation concept is applied to the problem of object recognition with several distributed sensors and it is shown that in binary object recognition the MAP object recognition also minimizes the mean-square error.
Abstract: The maximum a posteriori (MAP) estimation concept is applied to the problem of object recognition with several distributed sensors. It is shown that in binary object recognition the MAP object recognition also minimizes the mean-square error. Simulation results show that the performance of the MAP object recognition is, in general, at least as good as the best performance by the sensors used. >

14 citations

Patent
Hiroaki Ikeda1
09 Jul 2003
TL;DR: In this article, a re-recognition range is set based on the result of recognition using a first recognition unit, and character recognition by a second recognition unit is performed within the set range.
Abstract: A character recognition apparatus which performs character recognition with increased accuracy on a document image including plural languages. A re-recognition range is set based on the result of recognition using a first recognition unit, and character recognition by a second recognition unit is performed within the set range. In the re-recognition range, if a similarity of the result of re-recognition is higher than that by the first recognition unit, the result of recognition by the first recognition unit is replaced with the result of recognition by the second recognition unit.

14 citations

Proceedings ArticleDOI
01 Dec 2006
TL;DR: A Vector Quantization based bimodal (speech and face) biometric recognition method which delivers high performance amidst noise, illumination variations and occlusions (disguised mode) while requiring very little training data, memory storage and complexity of operation.
Abstract: We present a Vector Quantization based bimodal (speech and face) biometric recognition method which delivers high performance amidst noise, illumination variations and occlusions (disguised mode) while requiring very little training data, memory storage and complexity of operation. A transform VQ method delivers good face-recognition performance and a Text Dependent VQ method provides good recognition performance using speech. Simple fusion of two leads to a wider separation between the user-clusters in the combined feature space, leading to high performance.

14 citations

Proceedings ArticleDOI
01 Sep 2015
TL;DR: The goal of this work is to study the performance of the system in two cases: first, an optimal time functions-based system taking into account the information related to X and Y coordinates and pressure, which is the common practice (i.e. Standard System) and an extreme case not considering informationrelated to X, Y coordinate and their derivatives on the biometric system, which would be a much more robust system against attacks.
Abstract: Due to the high deployment of devices such as smartphones and tablets and their increasing popularity in our society, the use of biometric traits in commercial and banking applications through these novel devices as an easy, quick and reliable way to perform payments is rapidly increasing. The handwritten signature is one of the most socially accepted biometric traits in these sectors due to the fact that it has been used in financial and legal transitions for centuries. In this paper we focus on dynamic signature verification systems. Nowadays, most of the state-of-the-art systems are based on extracting information contained in the X and Y spatial position coordinates of the signing process, which is stored in the biometric templates. However, it is critical to protect this sensible information of the users signatures against possible external attacks that would allow criminals to perform direct attacks to a biometric system or carry out high quality forgeries of the users signatures. Following this problem, the goal of this work is to study the performance of the system in two cases: first, an optimal time functions-based system taking into account the information related to X and Y coordinates and pressure, which is the common practice (i.e. Standard System). Second, we study an extreme case not considering information related to X, Y coordinates and their derivatives on the biometric system (i.e. Secure System), which would be a much more robust system against attacks, as this critical information would not be stored anywhere. The experimental work is carried out using e-BioSign database which makes use of 5 devices in total. The systems considered in this work are based on Dynamic Time Warping (DTW), an elastic measure over the selected time functions. Sequential Forward Features Selection (SFFS) is applied as a reliable way to obtain an optimal time functions vector over a development subset of users of the database. The results obtained over the evaluation subset of users of the database show a similar performance for both Standard and Secure Systems. Therefore, the use of a Secure System can be useful in some applications such as banking in order to avoid the lost of important user information against possible external attacks.

14 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202310
202219
202122
202028
201925
201832