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| Offline Handwritten Signature Identification and Verification using Multi-Resolution Gabor Wavelet
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Source |
International Journal of Biometrics and Bioinformatics (IJBB) |
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Table of Contents |
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Complete Issue PDF(1.69MB) |
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Volume: 5 Issue: 4 |
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Pages: NULL |
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Publication
Date: September / October 2011 |
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ISSN
(Online): 1985-2347 |
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234 - 248 |
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Author(s) |
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Published
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05-10-2011 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
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| Keywords Abstract References Cited by Related Articles Collaborative
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KEYWORDS: Signature Identification, Signature Verification, Multi-resolution Analysis, Gabor Wavelet, Nearest Neighbour |
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| 1. Directory of Open Access Journals (DOAJ) |
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| In this paper, we are proposing a new method for offline (static) handwritten signature identification and verification based on Gabor wavelet transform. The whole idea is offering a simple and robust method for extracting features based on Gabor Wavelet which the dependency of the method to the nationality of signer has been reduced to its minimal. After pre-processing stage that contains noise reduction and signature image normalisation by size and rotation, a virtual grid is placed on the signature image. Gabor wavelet coefficients with different frequencies and directions are computed on each points of this grid and then fed into a classifier. The shortest weighted distance has been used as the classifier. The weight that is used as the coefficient for computing the shortest distance is based on the distribution of instances in each of signature classes.
As it was pointed out earlier, one of the advantages of this system is its capability of signature identification and verification of different nationalities; thus it has been tested on four signature dataset with different nationalities including Iranian, Turkish, South African and Spanish signatures. Experimental results and the comparison of the proposed system with other systems are consistent with desirable outcomes. Despite the use of the simplest method of classification i.e. the nearest neighbour, the proposed algorithm in comparison with other algorithms has very good capabilities. Comparing the results of our system with the accuracy of human\'s identification and verification, it shows that human identification is more accurate but our proposed system has a lower error rate in verification.
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Ferdowsi University of Mashhad
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| Mohamad Hoseyn Sigari : Colleagues
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| Muhammad Reza Pourshahabi : Colleagues
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| Hamid Reza Pourreza : Colleagues
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