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Author (up) Carrasco, M.; Toledo, PA.; Velazquez, R.; Bruno, OM. doi  openurl
  Title Automatic Stomatal Segmentation Based on Delaunay-Rayleigh Frequency Distance Type
  Year 2020 Publication Plants-Basel Abbreviated Journal Plants-Basel  
  Volume 9 Issue 11 Pages 1613  
  Keywords stomatal segmentation; image segmentation; Delaunay-Rayleigh frequency  
  Abstract The CO2 and water vapor exchange between leaf and atmosphere are relevant for plant physiology. This process is done through the stomata. These structures are fundamental in the study of plants since their properties are linked to the evolutionary process of the plant, as well as its environmental and phytohormonal conditions. Stomatal detection is a complex task due to the noise and morphology of the microscopic images. Although in recent years segmentation algorithms have been developed that automate this process, they all use techniques that explore chromatic characteristics. This research explores a unique feature in plants, which corresponds to the stomatal spatial distribution within the leaf structure. Unlike segmentation techniques based on deep learning tools, we emphasize the search for an optimal threshold level, so that a high percentage of stomata can be detected, independent of the size and shape of the stomata. This last feature has not been reported in the literature, except for those results of geometric structure formation in the salt formation and other biological formations.  
  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2223-7747 ISBN Medium  
  Area Expedition Conference  
  Notes Approved  
  Call Number UAI @ alexi.delcanto @ Serial 1273  
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