New method for feature extraction based on fractal behavior - IDRBT

1080 Y.Y. Tang et al. / Pattern Recognition 35 (2002) 1071–1081
Fig. 6. An example of handwritten signature verication.
dimension tells us much about geometrical properties,
such as the projection of sets, andwe have seen something
of the problems associatedwith calculating the
fractal dimensions. Clearly, dimensions are intimately
relatedto the study of fractal geometry. However, the
experiment results show that this approach allows us
to obtain new andinteresting descriptions of complex
patterns. In some situations, it has even already yielded
better results than “classical” <strong>method</strong>s. For all the cases,
dierences in fractal dimension can be found the signicative
values. We expect that the proposedfractal
<strong>method</strong>can also be used<strong>for</strong> improving the <strong>extraction</strong> and
classication of <strong>feature</strong>s in a pattern recognition system.
Acknowledgements
This work was supportedby research grants received
from the Research Grant Council (RGC) of Hong Kong
anda Faculty Research Grant (FRG) from Hong Kong
Baptist University.
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