IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v118y2015icp239-247.html
   My bibliography  Save this article

Entropic image segmentation of sessile drops over patterned acetate

Author

Listed:
  • Gómez-Lopera, J.F.
  • Martínez-Aroza, J.
  • Rodríguez-Valverde, M.A.
  • Cabrerizo-Vílchez, M.A.
  • Montes-Ruíz-Cabello, F.J.

Abstract

An entropic segmentation method is presented and applied to the contour detection of water drops over patterned surfaces. Jensen–Shannon divergence is computed from a double sliding window in the image to get a real number matrix, in which a region growing procedure is performed in a similar way to usual watershed. Then a region merging process is achieved, and the optimal configuration is selected to obtain the complete drop contour. Once the drop contour is detected from top-view images, the contact angle might be readily computed from the area enclosed by the contour and the drop volume.

Suggested Citation

  • Gómez-Lopera, J.F. & Martínez-Aroza, J. & Rodríguez-Valverde, M.A. & Cabrerizo-Vílchez, M.A. & Montes-Ruíz-Cabello, F.J., 2015. "Entropic image segmentation of sessile drops over patterned acetate," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 118(C), pages 239-247.
  • Handle: RePEc:eee:matcom:v:118:y:2015:i:c:p:239-247
    DOI: 10.1016/j.matcom.2014.11.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475414003061
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.matcom.2014.11.007?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. Ferdinand Österreicher & Igor Vajda, 2003. "A new class of metric divergences on probability spaces and its applicability in statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(3), pages 639-653, September.
    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. Martínez-Aroza, J. & Gómez-Lopera, J.F. & Blanco-Navarro, D. & Rodríguez-Camacho, J., 2021. "Clustered entropy for edge detection," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 620-645.

    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. Sagron, Ruth & Pugatch, Rami, 2021. "Universal distribution of batch completion times and time-cost tradeoff in a production line with arbitrary buffer size," European Journal of Operational Research, Elsevier, vol. 293(3), pages 980-989.
    2. Papastamoulis Panagiotis & Rattray Magnus, 2017. "Bayesian estimation of differential transcript usage from RNA-seq data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(5-6), pages 387-405, December.
    3. Yu, Xisheng, 2021. "A unified entropic pricing framework of option: Using Cressie-Read family of divergences," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    4. Yan Zhihua & Tang Xijin, 2020. "Exploring Evolution of Public Opinions on Tianya Club Using Dynamic Topic Models," Journal of Systems Science and Information, De Gruyter, vol. 8(4), pages 309-324, August.
    5. Leila M Naeni & Hugh Craig & Regina Berretta & Pablo Moscato, 2016. "A Novel Clustering Methodology Based on Modularity Optimisation for Detecting Authorship Affinities in Shakespearean Era Plays," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-27, August.
    6. Boussalis, Constantine & Dukalskis, Alexander & Gerschewski, Johannes, 2022. "Why It Matters What Autocrats Say: Assessing Competing Theories of Propaganda," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 70(3), pages 241-252.
    7. Osán, T.M. & Bussandri, D.G. & Lamberti, P.W., 2022. "Quantum metrics based upon classical Jensen–Shannon divergence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    8. Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2016. "Improved classi cation for compositional data using the $\alpha$-transformation," MPRA Paper 67657, University Library of Munich, Germany.
    9. Osán, Tristán M. & Bussandri, Diego G. & Lamberti, Pedro W., 2018. "Monoparametric family of metrics derived from classical Jensen–Shannon divergence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 336-344.
    10. Michail Tsagris & Simon Preston & Andrew T. A. Wood, 2016. "Improved Classification for Compositional Data Using the α-transformation," Journal of Classification, Springer;The Classification Society, vol. 33(2), pages 243-261, July.
    11. Tsagris, Michail, 2014. "The k-NN algorithm for compositional data: a revised approach with and without zero values present," MPRA Paper 65866, University Library of Munich, Germany.
    12. Tsagris, Michail, 2015. "A novel, divergence based, regression for compositional data," MPRA Paper 72769, University Library of Munich, Germany.
    13. Topsøe, Flemming, 2004. "Entropy and equilibrium via games of complexity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 340(1), pages 11-31.

    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:matcom:v:118:y:2015:i:c:p:239-247. 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/mathematics-and-computers-in-simulation/ .

    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.