DocumentCode
3442474
Title
Server-side reconstruction trajectory generation methods for hand written objects authentication - A comparative review
Author
Radhika, K.R. ; Sekhar, G.N. ; Venkatesha, M.K.
Author_Institution
Inf. Sci. & Eng., B.M.S. Coll. of Eng., Bangalore, India
fYear
2009
fDate
2-4 April 2009
Firstpage
211
Lastpage
215
Abstract
In online applications, there is a foreseeable explosive growth in biometric personal authentication systems which are covenant with a measurable behavioral trait. Hand written object [HO] verification is the process used to recognize an individual, which is intuitive reliable indicator. Verification of a HO as a biometric modality still is a challenging field of research, as number of online and offline commercial applications use modern acquisition devices. The employment of HO verification with technology still remains open for novel methods due to inter-class and intra-class variations. This paper discusses the trajectory generation [TG] methods applicable for any HO verification, such as character recognition, handwriting verification, style classification, shape recognition and signature recognition, which are suitable for latest trend of mobile-commerce and web-commerce applications.
Keywords
electronic commerce; handwriting recognition; handwritten character recognition; Web commerce; acquisition device; biometric modality; biometric personal authentication system; hand written object verification; hand written objects authentication; measurable behavioral trait; mobile commerce; server-side reconstruction trajectory generation method; Authentication; Biometrics; Character recognition; Data mining; Handwriting recognition; Information science; Personal digital assistants; Reliability engineering; Robotics and automation; Shape control; Beta-elliptical model; Lognormal models; Weibull model;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia Computing and Systems, 2009. ICMCS '09. International Conference on
Conference_Location
Ouarzazate
Print_ISBN
978-1-4244-3756-6
Electronic_ISBN
978-1-4244-3757-3
Type
conf
DOI
10.1109/MMCS.2009.5256700
Filename
5256700
Link To Document