Feature extraction by fractal dimensions

Author

Tang, Yuan Y. ; Tao, Yu

Author_Institution

Dept. of Comput. Sci., Hong Kong Baptist Univ., Kowloon, Hong Kong

fYear

1999

fDate

20-22 Sep 1999

Firstpage

217

Lastpage

220

Abstract

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

Keywords

dimensions; feature extraction; fractals; wavelet transforms; 2D pattern; Daubechies wavelet transformation; central projection approach; dimensionality reduction; divider dimensions; feature extraction; feature vector; fractal dimension; modified box-counting approach; nonself-intersecting curves; wavelet transformation sub-patterns; Computer science; Density functional theory; Feature extraction; Fractals; Image analysis; Pattern analysis; Pattern recognition; Research and development; Wavelet analysis; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 1999. ICDAR '99. Proceedings of the Fifth International Conference on

Conference_Location

Bangalore

Print_ISBN

0-7695-0318-7

Type

conf

DOI

10.1109/ICDAR.1999.791763

Filename

791763