TY - JOUR
T1 - Writer identification using fractal dimension of wavelet subbands in gabor domain
AU - He, Zhenyu
AU - You, Xinge
AU - Zhou, Long
AU - CHEUNG, Yiu Ming
AU - Du, Jianwei
N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - Writer identification is an important and active branch of biometrics, which means the methods for uniquely recognizing humans based upon their intrinsic physical or behavioral traits. In this paper, we propose one new method for off-line, text-independent writer identification by using the fractal dimension of wavelet subbands in Gabor domain of the handwriting images. In this method, the handwriting images are firstly decomposed into a series of Gabor subbands at different orientations and frequencies. Every Gabor subband is extended into one data sequence. Then, every sequence is decomposed into a series of wavelet subpatterns by wavelet transform. Afterwards, the mesh fractal dimensions of every wavelet subpattern are extracted as the feature for writer identification. Compared to the traditional Gabor method for off-line, text-independent writer identification, our method can extract more effective features to distinguish the handwritings, and hence achieve much better identification results.
AB - Writer identification is an important and active branch of biometrics, which means the methods for uniquely recognizing humans based upon their intrinsic physical or behavioral traits. In this paper, we propose one new method for off-line, text-independent writer identification by using the fractal dimension of wavelet subbands in Gabor domain of the handwriting images. In this method, the handwriting images are firstly decomposed into a series of Gabor subbands at different orientations and frequencies. Every Gabor subband is extended into one data sequence. Then, every sequence is decomposed into a series of wavelet subpatterns by wavelet transform. Afterwards, the mesh fractal dimensions of every wavelet subpattern are extracted as the feature for writer identification. Compared to the traditional Gabor method for off-line, text-independent writer identification, our method can extract more effective features to distinguish the handwritings, and hence achieve much better identification results.
KW - fractal dimension
KW - gabor
KW - wavelet
KW - Writer identification
UR - http://www.scopus.com/inward/record.url?scp=77954556306&partnerID=8YFLogxK
U2 - 10.3233/ICA-2010-0338
DO - 10.3233/ICA-2010-0338
M3 - Journal article
AN - SCOPUS:77954556306
SN - 1069-2509
VL - 17
SP - 157
EP - 165
JO - Integrated Computer-Aided Engineering
JF - Integrated Computer-Aided Engineering
IS - 2
ER -