An improved box-counting method for image fractal dimension estimation

Authors:
Jian Li;Qian Du;Caixin Sun
Affiliations:
State Key Laboratory of Power Transmission Equipment & System Security and New Technology, College of Electrical Engineering, Chongqing University, Chongqing 400044, China;Department of Electrical and Computer Engineering, Mississippi State University, MS 39762, USA;State Key Laboratory of Power Transmission Equipment & System Security and New Technology, College of Electrical Engineering, Chongqing University, Chongqing 400044, China
Venue:
Pattern Recognition
Year:
2009

Citing 11
Cited 5

Texture description and segmentation through fractal geometry

Computer Vision, Graphics, and Image Processing
Texture Segmentation Using Fractal Dimension

IEEE Transactions on Pattern Analysis and Machine Intelligence
Near optimum estimation of local fractal dimension for image segmentation

Pattern Recognition Letters
Chaos and Fractals

Chaos and Fractals
A new approach to estimate fractal dimensions of corrosion images

Pattern Recognition Letters
Coarse iris classification using box-counting to estimate fractal dimensions

Pattern Recognition
Multiple Resolution Texture Analysis and Classification

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fractal-Based Description of Natural Scenes

IEEE Transactions on Pattern Analysis and Machine Intelligence
Dimension estimation of discrete-time fractional Brownian motion with applications to image texture classification

IEEE Transactions on Image Processing
A maximum likelihood estimate for two-variable fractal surface

IEEE Transactions on Image Processing
Image segmentation and contour detection using fractal coding

IEEE Transactions on Circuits and Systems for Video Technology

Exploiting the synergy between fractal dimension and lacunarity for improved texture recognition

Signal Processing
Pattern recognition with cerebellar model articulation controller and fractal features on partial discharges

Expert Systems with Applications: An International Journal
Combining approaches for early diagnosis of breast diseases using thermal imaging

International Journal of Innovative Computing and Applications
Sonification of images for the visually impaired using a multi-level approach

Proceedings of the 4th Augmented Human International Conference
Box-Counting Dimension of Fractal Urban Form: Stability Issues and Measurement Design

International Journal of Artificial Life Research

Quantified Score

Hi-index	0.01

Visualization

Abstract

Fractal dimension (FD) is a useful feature for texture segmentation, shape classification, and graphic analysis in many fields. The box-counting approach is one of the frequently used techniques to estimate the FD of an image. This paper presents an efficient box-counting-based method for the improvement of FD estimation accuracy. A new model is proposed to assign the smallest number of boxes to cover the entire image surface at each selected scale as required, thereby yielding more accurate estimates. The experiments using synthesized fractional Brownian motion images, real texture images, and remote sensing images demonstrate this new method can outperform the well-known differential boxing-counting (DBC) method.