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Feature extraction by fractal dimensions
Tang Y.Y.; Tao Y.
1999
Source PublicationProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Pages217-220
AbstractIn this paper, the proposes a method that reduces the dimensionality of a 2D pattern by means of a central projection approach, and thereafter performs a Daubechies wavelet transformation on the derived 1D pattern to generate a set of wavelet transformation sub-patterns, namely curves that are non-self-intersecting. Further, from the resulting non-self-intersecting curves, the divider dimensions are compared with the modified box-counting approach. These divider dimensions constitute a new feature vector for the original 2D pattern, defined over the curve's fractal dimensions.
DOI10.1109/ICDAR.1999.791763
URLView the original
Language英語
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Document TypeConference paper
专题University of Macau
AffiliationHong Kong Baptist University
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GB/T 7714
Tang Y.Y.,Tao Y.. Feature extraction by fractal dimensions[C],1999:217-220.
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