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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.


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Proceedings Article
01 Jan 1998
TL;DR: The alternative approach to speech recognition proposed here is based on pseudo-articulatory representations (PARs), which can be described as approximations of distinctive features, and aims to establish a mapping between them and their acoustic specifications (in this case cepstral coefficients).
Abstract: The alternative approach to speech recognition proposed here is based on pseudo-articulatory representations (PARs), which can be described as approximations of distinctive features, and aims to establish a mapping between them and their acoustic specifications (in this case cepstral coefficients). This mapping which is used as the basis for recognition is first done for vowels. It is obtained using multiple regression analysis after all the vowels have been described in terms of phonetic features and an average cepstral vector has been calculated for each of them. Based on this vowel model, the PAR values are calculated for consonants. At this point recognition is performed using a brute search mechanism to derive PAR trajectories and subsequently dynamic programming to obtain a phone sequence. The results are not as good as when hidden Markov modelling is used, but very promising taking into account the early stage of the experiments and the novelty of the approach.

13 citations

Proceedings ArticleDOI
03 Apr 1990
TL;DR: The principle of trajectory space comparison for text-independent speaker recognition and some solutions to the space comparison problem based on vector quantization are presented and the comparison of the recognition rates of different solutions is reported.
Abstract: The principle of trajectory space comparison for text-independent speaker recognition and some solutions to the space comparison problem based on vector quantization are presented. The comparison of the recognition rates of different solutions is reported. The experimental system achieves a 99.5% text-independent speaker recognition rate for 23 speakers, using five phrases for training and five for test. A speaker-independent continuous speech recognition system is built in which this principle is used for speaker adaptation. >

13 citations

Proceedings ArticleDOI
15 Jul 2013
TL;DR: A virtual environment for the generation of complete threedimensional fingertip shapes is described and it is shown that the method is feasible and produces realistic three-dimensional samples which can effectively be processed by biometric recognition algorithms.
Abstract: Three-dimensional models of fingerprints obtained from contactless acquisitions have the advantages of reducing the distortion present in traditional contact-based samples and the effects of dirt on the finger and the sensor surface. Moreover, they permit to use a greater area for the biometric recognition. The design and test of three-dimensional reconstruction algorithms and contactless recognition methods require the collection of large databases. Since this task can be expensive and timeconsuming, some methods in the literature deal with the generation of synthetic biometric samples. At the best of our knowledge, however, there is only a preliminary study on the computation of small areas of synthetic three-dimensional fingerprints. In this paper, we extend our previous work and describe a virtual environment for the generation of complete threedimensional fingertip shapes, which can be useful for the research community working in the field of three-dimensional fingerprint biometrics. The method is based on image processing techniques and algorithms designed for biometric recognition. We validated the realism of the simulated models by comparing them with real contactless acquisitions. Results show that the method is feasible and produces realistic three-dimensional samples which can effectively be processed by biometric recognition algorithms.

13 citations

01 Jan 2011
TL;DR: Experimental result indicates that the proposed method achieved high accuracy rate in signature recognition.
Abstract: In this work a new offline signature recognition system based on Radon Transform, Fractal Dimension (FD) and Support Vector Machine (SVM) is presented. In the first step, projections of original signatures along four specified directions have been performed using radon transform. Then, FDs of four obtained vectors are calculated to construct a feature vector for each signature. These vectors are then fed into SVM classifier for recognition of signatures. In order to evaluate the effectiveness of the system several experiments are carried out. Offline signature database from signature verification competition (SVC) 2004 is used during all of the tests. Experimental result indicates that the proposed method achieved high accuracy rate in signature recognition.

13 citations

01 Jan 2004
TL;DR: A simple adaptive off-line signature recognition method based on the feature analysis of extracted significant strokes for a given signature, which correctly decides on the majority of tested patterns, which include both simple and skilled forgeries.
Abstract: This paper proposes a simple adaptive off-line signature recognition method based on the feature analysis of extracted significant strokes for a given signature. Our system correctly decides on the majority of tested patterns, which include both simple and skilled forgeries. The presence of possible doubtful signatures (those ones on which is difficult to decide) is also considered. Experimental results have shown a good trade-off between response time and reasonable accuracy of recognition results.

13 citations


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