A Fingerprint Image Segmentation Method Based on Fractal Dimension

Ming Xiang; Zhen Dong Cui; Yuan Hong Wu

doi:10.4028/www.scientific.net/AMR.461.299

Paper Titles

The Discharge Characteristics of PEO Films in K₂ZrF₆ with H₃PO₄ Electrolyte
p.277

Design of CO₂ Collection Node Based on ZigBee
p.281

Combining Item Rating Similarity and Item Classification Similarity for Better Recommendation Quality
p.289

Feasibility Analysis of Applying Thermal Insulation Composite Wall in Residential Buildings
p.293

A Fingerprint Image Segmentation Method Based on Fractal Dimension
p.299

Outcome-Based Earthquake early Warning
p.302

Applications of Yang-Fourier Transform to Local Fractional Equations with Local Fractional Derivative and Local Fractional Integral
p.306

Comparison of Earthquake Cases and China Public Safety Early Warning Information
p.311

Key Technology for CBR Maintenance Resources Requirement Analysis
p.316

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 461A Fingerprint Image Segmentation Method Based on...

A Fingerprint Image Segmentation Method Based on Fractal Dimension

Abstract:

Fractal analysis is becoming more and more popular in image segmentation community, in which the box-counting based fractal dimension estimations are most commonly used. In this paper, a novel fractal estimation algorithm is proposed. Both the proposed algorithm and the box-counting based methods have been applied to the segmentation of texture images. The comparison results demonstrate that the fractal estimation can differentiate texture images more effectively and provide more robust segmentations

You might also be interested in these eBooks

Advanced Building Materials and Structural Engineering

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 461)

Pages:

299-301

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.461.299

Citation:

Cite this paper

Online since:

February 2012

Authors:

Ming Xiang, Zhen Dong Cui, Yuan Hong Wu

Keywords:

Fingerprint, Fraction, Image Segment

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] A. P. Pentland, Fractal based description of natural scenes, IEEE Trans. Pattern Analysis and Machine Intell., 6 (1984) 661-674.

DOI: 10.1109/tpami.1984.4767591

Google Scholar

[2] A. Conci and L. H. Monteiro, Multifractal characterization of texture based segmentation, in Proc. IEEE Int. Conf. Image Processing, Vancouver, BC, Canada, Sep. 10–13, 2000, p.792–795.

DOI: 10.1109/icip.2000.901078

Google Scholar

[3] I. Reljin, B. Reljin, I. Pavlovic, and I. Rakocevic, Multifractal analysisof gray-scale images, in Proc. Mediterranean Electrotechnical Conf., May 29–31, 2000, p.490–493.

DOI: 10.1109/melcon.2000.879977

Google Scholar

[4] G. Du and T. S. Yeo, A novel multifractal estimation method and its application to remote image segmentation, IEEE Trans. Geosci. Remote Sens., vol. 40, no. 4, p.980–982, Jul. (2002).

DOI: 10.1109/tgrs.2002.1006395

Google Scholar

[5] Y. Liu and Y. Li, Image feature extraction and segmentation using fractal dimension, in Proc. ICSP, Seoul, Korea, Aug. 26–28, 1997, p.975–979.

Google Scholar

[6] T. A. Runkler and J. C. Bezdek, Image segmentation using fuzzy clustering with fractal features, in Proc. IEEE Int. Conf. Fuzzy Systems, Barcelona, Spain, Jul. 1–5, 1997, p.1393–1398.

DOI: 10.1109/fuzzy.1997.619747

Google Scholar

[7] J. You, S. Hungnahally, and A. Sattar, Fractional discrimination for texture image segmentation, in Proc. IEEE Int. Conf. Image Processing, Beijing, China, Oct. 28–31, 1997, p.220–223.

DOI: 10.1109/icip.1997.647743

Google Scholar

[8] R. Fazel-Rezai and W. Kinsner, Texture analysis and segmentation of images using fractals, in Proc. IEEE Canadian Conf. Electrical ComputerEngineering, May 9–12, 1999, p.786–791.

DOI: 10.1109/ccece.1999.808047

Google Scholar