Characteristics of Natural Scenes Related to the Fractal Dimension
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Imaging of Fractal Surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture description and segmentation through fractal geometry
Computer Vision, Graphics, and Image Processing
Artificial Intelligence
2D Shape Classification Using Multifractional Brownian Motion
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
A new method based on extension theory for partial discharge pattern recognition
WSEAS TRANSACTIONS on SYSTEMS
Unsupervised segmentation of ultrasonic liver images by multiresolution fractal feature vector
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Fast box-counting algorithm on GPU
Computer Methods and Programs in Biomedicine
Box-Counting Dimension of Fractal Urban Form: Stability Issues and Measurement Design
International Journal of Artificial Life Research
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Fractal geometry is becoming increasingly more important in the study of image characteristics. There are numerous methods available to estimate parameters from images of fractal surfaces. A very general technique to calculate numerous fractal features involves the estimation of the mass density function by box counting. The authors analyze the box-counting method, establish a lower bound for the box size, and indicate how algorithms can be improved to give better estimates of fractal features of images. This provides a theoretical basis for a heuristic approach used by C.A. Pickover and A.L. Khorasani (1986).