Results 251 to 260 of about 609,048 (290)

Signature recognition using vector quantization

Proceedings of the International Conference and Workshop on Emerging Trends in Technology, 2010
Handwritten Signatures are one of the widely used biometric traits for document authentication as well as human authorization. Various techniques have been implemented for Automatic Signature Recognition. In this paper we discuss the application of vector quantization to the problem of signature recognition.
H. B. Kekre, V. A. Bharadi, T. K. Sarode
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Offline Signature Recognition

2009
The most commonly used protection mechanisms today are based on either what a person possesses (e.g. an ID card) or what the person remembers (like passwords and PIN numbers). However, there is always a risk of passwords being cracked by unauthenticated users and ID cards being stolen, in addition to shortcomings like forgotten passwords and lost ID ...
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Online Signature Recognition

2009
Security is one of the major issues in today’s world and most of us have to deal with some sort of passwords in our daily lives; but, these passwords have some problems of their own. If one picks an easy-to-remember password, then it is most likely that somebody else may guess it.
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Shape signature for recognition process

Proceedings of the Seventeenth National Radio Science Conference. 17th NRSC'2000 (IEEE Cat. No.00EX396), 2002
Most of classical methods for shape recognition depend on classification of the object's features. This paper, gets round these classical methods, and presents a technique to determine a signature for any given closed shape to recognize it. It is simple in calculations, efficient in time and space complexity.
I.H. Khalifa, M.S.H. Fahmi, A.-E. Hassanien, H.A.R.M. Elsalamony   +3 more
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Development of novel signature architecture for signature recognition

Journal of Discrete Mathematical Sciences and Cryptography
The aim of this research paper is to propose a novel signature recognition system that utilizes deep learning techniques to accurately identify the name of a person based on their handwritten signature. The proposed architecture involves the use of a convolutional neural network (CNN) for feature extraction and a neural network for classification ...
Deepak Moud, Rakesh Kumar Saxena
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Neural Iris Signature Recognition (NISR)

2019
The security and the proper identification of individuals are vital requirements for many different applications. Biometric systems in general provide automatic recognition and identification of individuals taking advantage of the unique features of every individual.
Ali Mehdi, Safaa Ahmad, Rawand Abu Roza, Mohammed Alawairdhi, Mousa Al-Akhras   +4 more
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Vector signature for face recognition

2015 IEEE 19th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2015
In this paper, we proposed a vector signature scheme for face recognition. Using the signature, both the database size and communication bandwidth can be reduced. And the privacy of the face image is also improved. Some experimental implementation shows the potential of the new proposal.
Xiaochuan Lin, Ruizhong Wei
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Signature Forgery Recognition Using CNN

2020
This paper presents the recognition of hardwritten signatures. This is troublesome as even the human eye does not have that much visual capacity to distinguish everything in the manually written signature. It is hard for people to recognize the original and the fashioned ones. By utilizing profound realization which utilizes the refined reproduction of
Amit Chaurasia, Harsh Agarwal, Ankur Vishwakarma, Ashish Dwivedi, Arpit Sharma   +4 more
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Colour recognition using spectral signatures

Pattern Recognition Letters, 1987
Abstract Invariant spectral features suitable for colour identification over a range of lighting conditions are investigated. Histograms of the selected features are then used to form a spectral signature of similarly shaped objects enabling recognition.
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Online Signature-Based Biometric Recognition

2018
This chapter covers the online signature-based biometric recognition system, which includes fingerprint scanning, facial geometry, footprint scanning, retina and iris patterns, DNA, and heartbeat scans. It covers the background knowledge of signature verification system along with its classification.
Sudeep Tanwar, Mohammad S. Obaidat, Sudhanshu Tyagi, Neeraj Kumar   +3 more
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