Texture Description Using Fractal And Energy Features

    Authors

    T. Kasparis; N. S. Tzannes; M. Bassiouni;Q. Chen

    Comments

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    Abbreviated Journal Title

    Comput. Electr. Eng.

    Keywords

    Texture Segmentation; Texture Classification; Fractals; Textural Energy; Computer Science, Hardware & Architecture; Computer Science, ; Interdisciplinary Applications; Engineering, Electrical & Electronic

    Abstract

    The fractal dimension of a texture has been used in the past as a segmentation feature, but since it cannot sufficiently describe enough textural characteristics, additional features are needed. In this paper we demonstrate that by combining the fractal dimension with a a simple textural energy measure, a significant performance improvement is achieved compared to using each feature alone. The fractal dimension is computed using an efficient method that is also more accurate than most other popular methods, and the textural energy is easily computed using convolutional masks. Segmentation and classification of natural textures based on these two features is presented and the effect of additive noise is considered.

    Journal Title

    Computers & Electrical Engineering

    Volume

    21

    Issue/Number

    1

    Publication Date

    1-10-1995

    Document Type

    Article

    Language

    English

    First Page

    21

    Last Page

    32

    WOS Identifier

    WOS:A1995PW26300003

    ISSN

    0045-7906

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