New method for feature extraction based on fractal behavior

Yuan Y. Tang, Yu Tao*, Ernest C.M. Lam

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

83 Citations (Scopus)


In this paper, a novel approach to feature extraction based on fractal theory is presented as a powerful technique in pattern recognition. This paper presents a new fractal feature that can be applied to extract the feature of two-dimensional objects. It is constructed by a hybrid feature extraction combining wavelet analysis, central projection transformation and fractal theory. New fractal feature and fractal signatures are reported. A multiresolution family of the wavelets is also used to compute information conserving micro-features. We employed a central projection method to reduce the dimensionality of the original input pattern. A wavelet transformation technique to transform the derived pattern into a set of sub-patterns. Its fractal dimension can readily be computed, and to use the fractal dimension as the feature vectors. Moreover, a modified fractal signature is also used to distinguish the distinct handwritten signatures. We expect that the proposed fractal method can also be used for improving the extraction and classification of features in pattern recognition.

Original languageEnglish
Pages (from-to)1071-1081
Number of pages11
JournalPattern Recognition
Issue number5
Publication statusPublished - May 2002

Scopus Subject Areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

User-Defined Keywords

  • Box dimension
  • Central projection transformation
  • Feature extraction
  • Fractal geometry
  • Handwritten signature verification
  • Wavelet transformation


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