Automated efficient computation of crown transparency from tree silhouette images

Autor: Gérard Subsol, Yves Caraglio, Philippe Borianne
Přispěvatelé: Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), Image & Interaction (ICAR), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD [France-Sud]), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)
Rok vydání: 2017
Předmět:
Convex hull
Engineering drawing
010504 meteorology & atmospheric sciences
Computer science
Deep crown-indentation density
F62 - Physiologie végétale - Croissance et développement
Feuillage
forêt tropicale
02 engineering and technology
F50 - Anatomie et morphologie des plantes
01 natural sciences
santé des plantes
K01 - Foresterie - Considérations générales
0202 electrical engineering
electronic engineering
information engineering
Densité
U10 - Informatique
mathématiques et statistiques
[SDE.IE]Environmental Sciences/Environmental Engineering
Binary image
Forestry
Houppier
[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]
Computer Science Applications
Tree (data structure)
Imagerie
Transparency (graphic)
Forêt
020201 artificial intelligence & image processing
Computation
Lumière
Horticulture
Silhouette
Mesure
Foliage transparency
Arbre forestier
Densité du peuplement
0105 earth and related environmental sciences
Morphologie végétale
Méthode statistique
Tree crown
business.industry
Pattern recognition
15. Life on land
Weighting
Tree binary image
Artificial intelligence
U30 - Méthodes de recherche
business
Scale (map)
Agronomy and Crop Science
Zdroj: Computers and Electronics in Agriculture
Computers and Electronics in Agriculture, Elsevier, 2017, 133, pp.108-118. ⟨10.1016/j.compag.2016.12.011⟩
ISSN: 0168-1699
DOI: 10.1016/j.compag.2016.12.011
Popis: International audience; The transparency of trees is the most important indicator for a forest health assessment. This paper presents an efficient method for calculating the crown transparency coefficient from tree binary images. This coefficient is based on the automated quantification of the deep indentation, macro-hole and micro-hole densities. Circular structuring elements are introduced, among other things, to automatically find the significant biological size. The symmetric tree convex hull and the tree smoothed contour are defined to delineate the reference areas necessary to evaluate the above-mentioned densities. Statistical thresholds are proposed to eliminate human operator subjectivity, especially in the automated identification of anatomical elements such as soft and deep crown-indentations or macro and micro crown-holes. A point-wise transparency map is produced to better appreciate the origin of the visible skylight areas in the crown. The crown micro-hole density is calculated from the 0.1-to-0.5 transparency points, the crown macro-hole density from the 0.5-to-1 transparency points. We finally opt for weighting of the above three densities with regard to the importance of the symptoms they describe for a more relevant crown transparency coefficient. A comparative study on several trees from full-size and half-size binary images showed that our method is similar overall to the DSO and less sensitive to scale reduction.
Databáze: OpenAIRE
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