Offline Signature Verification Using Pixel Matching Technique
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TLDR
PMT (Pixel Matching Technique) is used to verify the signature of the user with the sample signature which is stored in the database and the performance of the proposed method has been compared with the existing ANN (Artificial Neural Network's) back-propagation method and SVM (Support Vector Machine) technique.About:
This article is published in Procedia Technology.The article was published on 2013-01-01 and is currently open access. It has received 58 citations till now. The article focuses on the topics: Signature recognition & Biometrics.read more
Citations
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Journal ArticleDOI
A framework for offline signature verification system: Best features selection approach
Muhammad Sharif,Muhammad Attique Khan,Muhammad Faisal,Mussarat Yasmin,Steven Lawrence Fernandes +4 more
TL;DR: A novel technique based on the idea of best features selection is introduced in this article for an offline verification system that is based on three accuracy measures as FAR, FRR and AER.
Journal ArticleDOI
Sensor-Based Continuous Authentication of Smartphones’ Users Using Behavioral Biometrics: A Contemporary Survey
TL;DR: The survey provides an overview of the current state-of-the-art approaches for continuous user authentication using behavioral biometrics captured by smartphones’ embedded sensors, including insights and open challenges for adoption, usability, and performance.
Posted Content
Sensor-based Continuous Authentication of Smartphones' Users Using Behavioral Biometrics: A Contemporary Survey
TL;DR: In this paper, the authors survey more than 140 behavioral biometric-based approaches for continuous user authentication, including motion-based methods (28 studies), gait-based techniques (19 studies), keystroke dynamics-based models (20 studies), touch gesture-based method (29 studies), voice-based model (16 studies), and multimodal-based approach (34 studies).
Journal ArticleDOI
Offline Signature Recognition Using Image Processing Techniques and Back Propagation Neuron Network System
TL;DR: In this paper, an offline signature recognition using back propagation neuron network system and image processing techniques has been proposed, which involves RGB2Gray conversion, filtering, adjusting, thresholding followed by canny edge detection and at the last image scaling applied to reduce the processing time.
Book ChapterDOI
New Fast Algorithm for the Dynamic Signature Verification Using Global Features Values
TL;DR: The algorithm proposed in this paper is a faster version of the method proposed earlier and resigned from using evolutionary selection of global features and standardized working of the classifier in the context of all users.
References
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Book
The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Journal ArticleDOI
Support-Vector Networks
Corinna Cortes,Vladimir Vapnik +1 more
TL;DR: High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated and the performance of the support- vector network is compared to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.
Journal ArticleDOI
Offline geometric parameters for automatic signature verification using fixed-point arithmetic
TL;DR: A set of geometric signature features for offline automatic signature verification based on the description of the signature envelope and the interior stroke distribution in polar and Cartesian coordinates are presented.
Proceedings ArticleDOI
Off-line signature verification using HMM for random, simple and skilled forgeries
TL;DR: The experiments have shown that the error rates of the simple and random forgery signatures are very closed, and this reflects the real applications in which the simple forgeries represent the principal fraudulent case.
Journal ArticleDOI
Off-line signature verification by the tracking of feature and stroke positions
TL;DR: The proposed system compares favorably with other methods and outperforms the volunteers when it comes to verifying the authenticity of a signature.