IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v581y2021ics0378437121004659.html
   My bibliography  Save this article

Lacunarity exponent and Moran index: A complementary methodology to analyze AFM images and its application to chitosan films

Author

Listed:
  • Pinto, Erveton P.
  • Pires, Marcelo A.
  • Matos, Robert S.
  • Zamora, Robert R.M.
  • Menezes, Rodrigo P.
  • Araújo, Raquel S.
  • de Souza, Tiago M.

Abstract

In this work, we developed new scripts to calculate the lacunarity exponent and Moran’s index of Atomic Force Microscopy (AFM) images. The lacunarity exponent was estimated by combining the Otsu binarization and gliding-box algorithm, and Moran index was introduced to evaluate the surfaces’ spatial autocorrelation. Developed scripts were first validated using numerical simulation of self-similar fractal and self-affine isotropic surfaces. Then, we successfully synthesized chitosan films with different glycerol concentrations and used the lacunarity and Moran’s index for a thorough characterization. The validation of the proposed scripts using simulated Sierpinski Carpets and 3D artificial surfaces showed promising potential for analyzing AFM images. Finally, the methodology application to AFM images of chitosan films suggested that lacunarity analysis and Moran index determination could complement thin films’ quality processing control.

Suggested Citation

  • Pinto, Erveton P. & Pires, Marcelo A. & Matos, Robert S. & Zamora, Robert R.M. & Menezes, Rodrigo P. & Araújo, Raquel S. & de Souza, Tiago M., 2021. "Lacunarity exponent and Moran index: A complementary methodology to analyze AFM images and its application to chitosan films," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
  • Handle: RePEc:eee:phsmap:v:581:y:2021:i:c:s0378437121004659
    DOI: 10.1016/j.physa.2021.126192
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437121004659
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2021.126192?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yanguang Chen, 2013. "New Approaches for Calculating Moran’s Index of Spatial Autocorrelation," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-14, July.
    2. Dong-heng Xie & Ming Lu & Yong-fang Xie & Duan Liu & Xiong Li, 2019. "A fast threshold segmentation method for froth image base on the pixel distribution characteristic," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-18, January.
    3. Dias, M.R.B. & Dornelas, D. & Balthazar, W.F. & Huguenin, J.A.O. & da Silva, L., 2017. "Lacunarity study of speckle patterns produced by rough surfaces," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 328-336.
    4. Taraschi, Giovanni & Florindo, Joao B., 2020. "Computing fractal descriptors of texture images using sliding boxes: An application to the identification of Brazilian plant species," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    5. Breslin, M.C. & Belward, J.A., 1999. "Fractal dimensions for rainfall time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 48(4), pages 437-446.
    6. Nasehnejad, Maryam & Nabiyouni, G. & Gholipour Shahraki, Mehran, 2018. "Thin film growth by 3D multi-particle diffusion limited aggregation model: Anomalous roughening and fractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 135-147.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Zhiwei & Wang, Jianjian & Yuan, Meng & Wang, Zhongyu & Feng, Pingfa & Feng, Feng, 2022. "An indicator to quantify the complexity of signals and surfaces based on scaling behaviors transcending fractal," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).
    2. Yajing Liu & Shuai Zhou & Ge Zhang, 2023. "Spatio-Temporal Dynamics and Driving Forces of Multi-Scale Emissions Based on Nighttime Light Data: A Case Study of the Pearl River Delta Urban Agglomeration," Sustainability, MDPI, vol. 15(10), pages 1-24, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Francisco Gerardo Benavides-Bravo & Dulce Martinez-Peon & Ángela Gabriela Benavides-Ríos & Otoniel Walle-García & Roberto Soto-Villalobos & Mario A. Aguirre-López, 2021. "A Climate-Mathematical Clustering of Rainfall Stations in the Río Bravo-San Juan Basin (Mexico) by Using the Higuchi Fractal Dimension and the Hurst Exponent," Mathematics, MDPI, vol. 9(21), pages 1-11, October.
    2. Huang, Wei, 2019. "Forest condition change, tenure reform, and government-funded eco-environmental programs in Northeast China," Forest Policy and Economics, Elsevier, vol. 98(C), pages 67-74.
    3. Sadia Basar & Mushtaq Ali & Gilberto Ochoa-Ruiz & Mahdi Zareei & Abdul Waheed & Awais Adnan, 2020. "Unsupervised color image segmentation: A case of RGB histogram based K-means clustering initialization," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-21, October.
    4. Ffion Carney, 2021. "Linking Loyalty Card Data to Public Transport Data to Explore Mobility and Social Exclusion in the Older Population," Sustainability, MDPI, vol. 13(11), pages 1-19, May.
    5. Guerreiro, Gertrudes & Caleiro, António, 2014. "A convergência espacial do conhecimento em Portugal [The spatial convergence of knowledge in Portugal]," MPRA Paper 56176, University Library of Munich, Germany.
    6. Rakin Abrar & Showmitra Kumar Sarkar & Kashfia Tasnim Nishtha & Swapan Talukdar & Shahfahad & Atiqur Rahman & Abu Reza Md Towfiqul Islam & Amir Mosavi, 2022. "Assessing the Spatial Mapping of Heat Vulnerability under Urban Heat Island (UHI) Effect in the Dhaka Metropolitan Area," Sustainability, MDPI, vol. 14(9), pages 1-24, April.
    7. Gertrudes Saúde Guerreiro & António Bento Caleiro, 2016. "The Spatial Convergence of Knowledge in Portugal," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 6(1), pages 1082-1082.
    8. Miao Yu & Dong Liu & Jean Dieu Bazimenyera, 2013. "Diagnostic Complexity of Regional Groundwater Resources System Based on time series fractal dimension and Artificial Fish Swarm Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 1897-1911, May.
    9. Yanguang Chen, 2016. "Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-19, January.
    10. Liu, Yan-Ping & Wang, Lin & Zhang, Feng & Wang, Rui-Wu, 2020. "Diffusion sustains cooperation via forming diverse spatial patterns in prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 375(C).
    11. Borys, Przemyslaw, 2020. "Long term Hurst memory that does not die at long observation times—Deterministic map to describe ion channel activity," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    12. Zhenfang He & Yaonan Zhang & Qingchun Guo & Xueru Zhao, 2014. "Comparative Study of Artificial Neural Networks and Wavelet Artificial Neural Networks for Groundwater Depth Data Forecasting with Various Curve Fractal Dimensions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(15), pages 5297-5317, December.
    13. Yolanda Caballero & Ramón Giraldo & Jorge Mateu, 2022. "A spatial randomness test based on the box-counting dimension," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(3), pages 499-524, September.
    14. Inna MANAEVA & Anna TKACHEVA & Elena CHENTSOVA & Elena ILYICHEVA, 2021. "Assessment Of The Interconnectedness Of Cities In The Russian Far East," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(2), pages 123-133, June.
    15. Salcedo-Sanz, S. & Cuadra, L., 2019. "Hybrid L-systems–Diffusion Limited Aggregation schemes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 592-605.
    16. Francesco Tolu & Mario Palermo & Maria Pina Dore & Alessandra Errigo & Ana Canelada & Michel Poulain & Giovanni Mario Pes, 2019. "Association of endemic goitre and exceptional longevity in Sardinia: evidence from an ecological study," European Journal of Ageing, Springer, vol. 16(4), pages 405-414, December.
    17. Ke Fang, 2022. "Threshold segmentation of PCB defect image grid based on finite difference dispersion for providing accuracy in the IoT based data of smart cities," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 121-131, March.
    18. Dias, M.R.B. & Junior, A.O. Castro & Dias, C.P. & de Carvalho, S.A. & Huguenin, J.A.O. & da Silva, L., 2019. "Monitoring defects of a moving metallic surface through Tsallis entropic segmentation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    19. Dong Liu & Mingjie Luo & Qiang Fu & Yongjia Zhang & Khan M. Imran & Dan Zhao & Tianxiao Li & Faiz M. Abrar, 2016. "Precipitation Complexity Measurement Using Multifractal Spectra Empirical Mode Decomposition Detrended Fluctuation Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 505-522, January.
    20. Dong Liu & Mingjie Luo & Qiang Fu & Yongjia Zhang & Khan Imran & Dan Zhao & Tianxiao Li & Faiz Abrar, 2016. "Precipitation Complexity Measurement Using Multifractal Spectra Empirical Mode Decomposition Detrended Fluctuation Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 505-522, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:581:y:2021:i:c:s0378437121004659. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.