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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 Jan 2001
TL;DR: The concept of using codebooks of curves to characterise a persons handwriting, similar to the successful methods by which handwriting has been applied to speech recognition, is considered and assessed.
Abstract: In this paper we consider and assess the concept of using codebooks of curves to characterise a persons handwriting. This is similar to the successful methods by which handwriting has been applied to speech recognition. The handwritten signatures are scanned as binary images at 200 dpi, thinned to a single pixel width and characterised as a set of curves. Matching of signatures is achieved using a curve similarity measure. Experiments on a set of 120 handwritten signatures from six writers (20 per writer), including some forgeries, indicate the technique has potential. Whilst it does not currently perform as well as state-of-the-art signature verifiers there are numerous improvements that can be made to the technique. A number of refinements are proposed for discussion and further research.

3 citations

Journal Article
TL;DR: The distances measure of DTW is improved and the problem that nonlinear warping of time series of on-line signature is solved, making it suitable to use On-line hand-written Signature as a mothod of identity verification.
Abstract: With the development of computer network and biometric identification technology,identity verification with biologic characteristic feeds the need of the information age.Hand-written signature verification becomes a kind of the most acceptable way of identity verification because of it as the sign of authorization for a long time.In this paper,the distances measure of DTW is improved.Based on the characteristics of the shape of the time series itself,the problem that nonlinear warping of time series of on-line signature is solved.The experiment result is the ERR 3.0% when skilled forgeries are used.It is suitable to use On-line hand-written Signature as a mothod of identity verification.

3 citations

01 Jan 2015
TL;DR: The objective of this paper is towards implementing the Iris Recognition System (IRS) for ensuring security as well as safety of owner of the automobile.
Abstract: The objective of this paper is towards implementing the Iris Recognition System (IRS) for ensuring security as well as safety of owner of the automobile. Iris Recognition is a method of biometric authentication that employs pattern recognition techniques based on iris images of an individual's eyes. It is regarded as the most stable, reliable and accurate biometric identification system available. From studies, it is found that algorithms developed by Daugman produce perfect recognition rates. The Iris Recognition System consists of the following steps; Image Acquisition, Image Pre-Processing which involves image segmentation and normalization, then Feature Extraction and finally matching the processed image with database. The first two steps for Iris Recognition were performed successfully in MATLAB®. The edges of iris and pupil were detected using Canny Edge Detection technique and results were plotted. The state of drowsiness can also be detected by observing the closing of eyes which can ensure in safety of driver. Therefore, Iris Recognition is considered to be reliable and accurate biometric technique for authentication of driver in automobile.

3 citations

Proceedings ArticleDOI
29 Apr 2013
TL;DR: The purpose of this technical report is for comparing different iris recognition systems based on their performance.
Abstract: Biometric identification system is used for the automatic identification of an individual based on the unique characteristics or features possessed by an individual. Many Biometric Technologies are available today. Iris Recognition System is the most reliable and accurate Biometric identification system available. Iris Recognition is the identification of an individual based on iris features. In the past few years many methods are used to improve the performance of iris recognition systems. These methods mainly focused on the robustness, accuracy and rapidity of iris recognition systems. The purpose of this technical report is for comparing different iris recognition systems based on their performance.

3 citations

Patent
11 Aug 2008
TL;DR: In this paper, a method of preprocessing biometric parameters acquired from human faces, voices, fingerprints, and irises to use them for user authentication and access control is proposed.
Abstract: PROBLEM TO BE SOLVED: To provide a method of preprocessing biometric parameters acquired from human faces, voices, fingerprints, and irises to use them for user authentication and access control. SOLUTION: Since the biometric parameters are continuous and vary from one reading to the next, syndrome codes are used to discriminate biometric syndrome vectors. The biometric syndrome vectors can be stored securely while the variability specific to the biometric data is permitted. The stored biometric syndrome vectors are decoded during user authentication using biometric parameters acquired at that time. The syndrome codes can also be used to encrypt and decrypt data. The biometric parameters can be pre-processed to form a binary representation having a set of predetermined statistical properties given under a set of binary logical conditions. COPYRIGHT: (C)2009,JPO&INPIT

3 citations


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