NDLI: Feature selection and indexing of online signatures

Content Provider	IEEE Xplore Digital Library
Author	Nagasundara, K.B. Guru, D.S. Manjunath, S.
Copyright Year	2012
Description	Author affiliation: Department of Studies in Computer Science, University of Mysore, Manasagangotri, India (Nagasundara, K.B.; Guru, D.S.; Manjunath, S.)
Abstract	In this paper, we propose a model for feature selection and indexing of online signatures based person identification. For representation of online signatures, a set of 100 global features of MCYT online signature database is considered. However, MCYT based features are high dimension features which significantly increases the response time and space requirements for signature identification process. To overcome this problem, multi cluster feature selection method is proposed to reduce the dimensionality by finding a relevant feature subset. Moreover, in some applications, where the database is supposed to be very large, the identification process typically has an unacceptably long response time. A solution to speed up the identification process is to design an indexing model prior to identification which reduces the number of candidate hypotheses to be considered during matching by the identification algorithm. Hence in this paper, Kd-tree based indexing model is designed for online signatures based person identification. The experimental results reveal that the proposed model works more efficiently both in terms of time and accuracy.
Starting Page	408
Ending Page	414
File Size	423300
Page Count	7
File Format	PDF
ISBN	9781467351140
e-ISBN	9781467351164
DOI	10.1109/HIS.2012.6421369
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-04
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biometrics Feature Selection Handwriting recognition Accuracy Biometrics (access control) Multi Cluster Feature Selection Feature extraction Vectors Online Signatures Kd-tree Person Identification Indexing
Content Type	Text
Resource Type	Article

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