Offline Handwritten Signature Identification and Verification Using Multi-Resolution Gabor Wavelet
نویسنده:
, , , , ,سال
: 2011
چکیده: 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.
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.
کلیدواژه(گان): Signature Identification,Signature Verification,Multi-Resolution Analysis,Gabor
Wavelet,Nearest Neighbour
کالکشن
:
-
آمار بازدید
Offline Handwritten Signature Identification and Verification Using Multi-Resolution Gabor Wavelet
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contributor author | محمدحسین سیگاری | en |
contributor author | محمدرضا پور شهابی | en |
contributor author | حمیدرضا پوررضا | en |
contributor author | Mohamad Hoseyn Sigari | fa |
contributor author | Muhammad Reza Pourshahabi | fa |
contributor author | Hamid Reza Pourreza | fa |
date accessioned | 2020-06-06T13:06:39Z | |
date available | 2020-06-06T13:06:39Z | |
date issued | 2011 | |
identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/3342001 | |
description abstract | 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. | en |
language | English | |
title | Offline Handwritten Signature Identification and Verification Using Multi-Resolution Gabor Wavelet | en |
type | Journal Paper | |
contenttype | External Fulltext | |
subject keywords | Signature Identification | en |
subject keywords | Signature Verification | en |
subject keywords | Multi-Resolution Analysis | en |
subject keywords | Gabor Wavelet | en |
subject keywords | Nearest Neighbour | en |
journal title | International Journal of Biometric and Bioinformatics | fa |
pages | 234-248 | |
journal volume | 5 | |
journal issue | 4 | |
identifier link | https://profdoc.um.ac.ir/paper-abstract-1025855.html | |
identifier articleid | 1025855 |