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Texture Analysis in Images with Differential Box Counting Algorithm

V. Lakshmi Praba1 , S. Esakkiammal2

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-08 , Page no. 83-86, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si8.8386

Online published on Apr 10, 2019

Copyright © V. Lakshmi Praba, S. Esakkiammal . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: V. Lakshmi Praba, S. Esakkiammal, “Texture Analysis in Images with Differential Box Counting Algorithm,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.08, pp.83-86, 2019.

MLA Style Citation: V. Lakshmi Praba, S. Esakkiammal "Texture Analysis in Images with Differential Box Counting Algorithm." International Journal of Computer Sciences and Engineering 07.08 (2019): 83-86.

APA Style Citation: V. Lakshmi Praba, S. Esakkiammal, (2019). Texture Analysis in Images with Differential Box Counting Algorithm. International Journal of Computer Sciences and Engineering, 07(08), 83-86.

BibTex Style Citation:
@article{Praba_2019,
author = {V. Lakshmi Praba, S. Esakkiammal},
title = {Texture Analysis in Images with Differential Box Counting Algorithm},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {07},
Issue = {08},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {83-86},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=922},
doi = {https://doi.org/10.26438/ijcse/v7i8.8386}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i8.8386}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=922
TI - Texture Analysis in Images with Differential Box Counting Algorithm
T2 - International Journal of Computer Sciences and Engineering
AU - V. Lakshmi Praba, S. Esakkiammal
PY - 2019
DA - 2019/04/10
PB - IJCSE, Indore, INDIA
SP - 83-86
IS - 08
VL - 07
SN - 2347-2693
ER -

           

Abstract

Fractal dimension is a one of the vital parameters in fractal geometry that find applications in the area of image processing. Image analysis is a high-level image processing technique which includes texture analysis. Texture analysis characterizes the regions in an image, based on their texture content. It categorizes texture qualities as roughness, smoothness, silkiness, bumpiness, etc. The image intensities are transformed to fractal dimension domain to carry out texture analysis. In this paper, determining the texture for two images- smooth image and coarse image is considered. Differential Box Counting algorithm is applied in the considered two images with different textures. The performance metrics considered are, fractal dimension average, fractal dimension standard deviation and lacunarity. The differential box counting algorithm with different pixels from different regions of the same image is implemented and the obtained results are analyzed.

Key-Words / Index Term

Image processing, Box-Counting, Texture Analysis, Fractal Dimension, Lacunarity

References

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