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Entropic image segmentation of sessile drops over patterned acetate

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  • 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
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    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.
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    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.

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