An Improved Disk-Counting Algorithm for Estimating Dimension of IFS-Based Fractal Image

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Author(s) Salau Tajudeen Abiola O. | Bodija Yusuf,Tella Olawale Ismail | Quadri Olatunji Oluwakemi
Pages 347-356
Volume 5
Issue 7
Date July, 2016
Keywords Fractal, Fractal Dimension, Disk-Counting Method, Iterated Function System

Fractal shapes are characterized using fractal dimension and has application in image quality assessment, texture segmentation, shape classification, data mining, and graphic analysis in many disciplines. A previous research established that the disk-counting method produces better results relative to analytical fractal dimension than the box counting method in estimating the fractal dimension of selected fractals generated using the Iterated Function System (IFS). However, this study presents better estimated disk dimension for IFS-based fractal images based on an improved disk-counting method. The improved algorithm was verified on twenty (20) fractal images generated using appropriate IFS-functions. Although the algorithm takes longer simulation time relative to its counterpart, it was however found to be less error prone and therefore highly recommended whenever accuracy and reliability are needed.

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