New method of feature extraction using fractals and wavelets

Yuan Y. Tang, Yu Tao*, Jin Tao, Dihua Xi

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

2 Citations (Scopus)


As the interest in fractal geometry rises, the applications are getting more and more numerous in many domains. This paper deals with the problem of recognizing and classification to optical character recognition. For this purpose, we present a new method of feature extraction based on the principles of fractal geometry and wavelet. This allows us to establish a classification of Chinese character in order to apply to each of the isolated categories the most adapt recognition methods.

In particular, the proposed method reduces the dimensionality of a two-dimensional pattern by way of a central projection approach, and thereafter, performs Daubechies' wavelet transformation on the derived one-dimensional 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 computed with modified box-counting approach. These divider dimensions constitute a new feature vector for the original two-dimensional pattern, defined over the curve's fractal dimensions.

We have conducted several experiments in which a set of printed alphanumeric symbols and Chinese characters of varying fonts and orientation were classified, based on the formulation of our new feature vector. The results obtained from these experiments have consistently shown the character recognition method with the proposed feature vector can yield an excellent classification rate 100%.
Original languageEnglish
Title of host publicationOptical Pattern Recognition X
EditorsDavid P. Casasent, Tien-Hsin Chao
Number of pages11
ISBN (Print)0819431893
Publication statusPublished - 9 Mar 1999
EventAerosense 1999 - Orlando, United States
Duration: 5 Apr 19999 Apr 1999

Publication series

NameSPIE Proceedings
ISSN (Print)0277-786X


ConferenceAerosense 1999
Country/TerritoryUnited States
Internet address

User-Defined Keywords

  • Wavelets
  • Fractal analysis
  • Feature extraction
  • Pattern recognition
  • Wavelet transforms
  • Optical character recognition
  • Analytical research
  • Binary data
  • Feature selection
  • Image analysis
  • Fractal dimension
  • Wavelet transformation
  • Character recognition
  • Classification


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