Fractal Dimension of GrayScale Images

  • Soumya Ranjan Nayak
  • Jibitesh Mishra
  • Pyari Mohan Jena
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 710)

Abstract

Fractal dimension (FD) is a necessary aspect for characterizing the surface roughness and self-similarity of complex objects. However, fractal dimension gradually established its importance in the area of image processing. A number of algorithms for estimating fractal dimension of digital images have been reported in many literatures. However, different techniques lead to different results. Among them, the differential box-counting (DBC) was most popular and well-liked technique in digital domain. In this paper, we have presented an efficient differential box-counting mechanism for accurate estimation of FD with less fitting error as compared to existing methods like original DBC, relative DBC (RDBC), and improved box-counting (IBC) and improved DBC (IDBC). The experimental work is carried out by one set of fourteen Brodatz images. From this experimental result, we found that the proposed method performs best among the existing methods in terms of less fitting error.

Keywords

Fractal dimension DBC RDBC IBC IDBC Grayscale image 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Soumya Ranjan Nayak
    • 1
  • Jibitesh Mishra
    • 2
  • Pyari Mohan Jena
    • 3
  1. 1.Department of Information TechnologyCollege of Engineering and TechnologyBhubaneswarIndia
  2. 2.Department of Computer Science and ApplicationCollege of Engineering and TechnologyBhubaneswarIndia
  3. 3.Department of Computer Science and EngineeringCollege of Engineering and TechnologyBhubaneswarIndia

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