Efficient fractal method for texture classification

Author

Popescu, Andreea Lavinia ; Popescu, Dan ; Ionescu, Radu Tudor ; Angelescu, Nicoleta ; Cojocaru, Romeo

Author_Institution

Fac. of Autom. Control & Comput. Sci., Politeh. Univ. of Bucharest, Bucharest, Romania

fYear

2013

fDate

26-27 Aug. 2013

Firstpage

44

Lastpage

49

Abstract

This paper presents an alternative approach to classical box counting algorithm for fractal dimension estimation. Irrelevant data are eliminated from input sequences of the algorithm and a new fractal dimension, called efficient fractal dimension (EFD), which is based on the remaining sequences is calculated. The discriminating capacity and the time efficiency of EFD are evaluated in comparison with fractal dimension (FD) computed by box counting both theoretically and empirically. The results revealed that EFD is better than FD for texture identification and classification.

Keywords

fractals; image classification; image texture; EFD time efficiency; classical box counting algorithm; discriminating capacity; efficient fractal dimension; fractal dimension estimation; fractal method; input sequence; texture classification; texture identification; Accuracy; Correlation; Estimation; Feature extraction; Fractals; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems and Computer Science (ICSCS), 2013 2nd International Conference on

Conference_Location

Villeneuve d´Ascq

Print_ISBN

978-1-4799-2020-4

Type

conf

DOI

10.1109/IcConSCS.2013.6632021

Filename

6632021