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Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/323

Title: Signature verification using multiple neural classifiers
Authors: Bajaj, Reena
Chaudhury, Santanu
Keywords: Signature verification
Projection moments
Envelopes
Neural net
Combination of classifiers
Issue Date: 1997
Citation: Pattern Recognition, 30(1), 1-7
Abstract: This paper is concerned with signature verification. Three different types of global features have been used for the classification of signatures. Feed-forward neural net based classifiers have been used. The features used for the classification are projection moments and upper and lower envelope based characteristics. Output of the three classifiers is combined using a connectionist scheme. Combination of these feature based classifiers for signature verification is the unique feature of this work. Experimental results show that combination of the classifiers increases reliability of the recognition results.
URI: http://eprint.iitd.ac.in/dspace/handle/2074/323
Appears in Collections:Electrical Engineering

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