Sreeraj, M; Sumam, Mary Idicula(IEEE, December 7, 2012)
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Abstract:
The span of writer identification extends to broad
domes like digital rights administration, forensic expert decisionmaking
systems, and document analysis systems and so on. As the
success rate of a writer identification scheme is highly dependent
on the features extracted from the documents, the phase of
feature extraction and therefore selection is highly significant for
writer identification schemes. In this paper, the writer
identification in Malayalam language is sought for by utilizing
feature extraction technique such as Scale Invariant Features
Transform (SIFT).The schemes are tested on a test bed of 280
writers and performance evaluated
Sreeraj, M; Sumam, Mary Idicula(Association for Computer Science and Telecommunica, May , 2011)
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Abstract:
This paper presents a writer identification scheme for Malayalam documents. As the accomplishment rate of a scheme is highly dependent on the features extracted from the documents, the process of feature selection and extraction is highly relevant. The paper describes a set of novel features exclusively for Malayalam language. The features were studied in detail which resulted in a comparative study of all the features. The features are fused to form the feature vector or knowledge vector. This knowledge vector is then used in all the phases of the writer identification scheme. The scheme has been tested on a test bed of 280 writers of which 50 writers having only one page, 215 writers with at least 2 pages and 15 writers with at least 4 pages. To perform a comparative evaluation of the scheme the test is conducted using WD-LBP method also. A recognition rate of around 95% was obtained for the proposed approach
Sreeraj, M; Dr.Sumam Mary,Idicula(Cochin University Of Science And Technology, July 30, 2012)
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Abstract:
Handwriting is an acquired tool used for communication of one's
observations or feelings. Factors that inuence a person's handwriting not
only dependent on the individual's bio-mechanical constraints, handwriting
education received, writing instrument, type of paper, background, but
also factors like stress, motivation and the purpose of the handwriting.
Despite the high variation in a person's handwriting, recent results from
different writer identification studies have shown that it possesses sufficient
individual traits to be used as an identification method.
Handwriting as a behavioral biometric has had the interest of researchers
for a long time. But recently it has been enjoying new interest due to an
increased need and effort to deal with problems ranging from white-collar
crime to terrorist threats. The identification of the writer based on a piece
of handwriting is a challenging task for pattern recognition. The main
objective of this thesis is to develop a text independent writer identification
system for Malayalam Handwriting. The study also extends to developing a
framework for online character recognition of Grantha script and Malayalam
characters
Description:
Department of Computer Science, Cochin University of Science and
Technology