DocumentCode :
456910
Title :
2D and 3D Vegetation Resource Parameters Assessment using Marked Point Processes
Author :
Perrin, Guillaume ; Descombes, Xavier ; Zerubia, Josiane
Author_Institution :
INRIA
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
1
Lastpage :
4
Abstract :
High resolution aerial and satellite images of forests have a key role to play in natural resource management. As they enable to study forests at the scale of trees, it is now possible to get a more accurate evaluation of the forest resources, from which can be deduced information on biodiversity and ecological sustainability. In that prospect, automatic algorithms are needed to give a further exploitation of the data and to assist human operators. In this paper, we present a stochastic geometry approach to extract 2D and 3D parameters of the trees, by modelling the stands as some realizations of a marked point process of ellipses or ellipsoids, whose points are the positions of the trees and marks their geometric features. This approach gives also the number of stems, their position, and their size. It is an energy minimization problem, where the energy embeds a regularization term (prior density), which introduces some interactions between the objects, and a data term, which links the objects to the features to be extracted. Results are shown on aerial images provided by the French National Forest Inventory (IFN)
Keywords :
environmental science computing; feature extraction; forestry; stereo image processing; stochastic processes; vegetation; 2D images; 3D images; aerial images; biodiversity; ecological sustainability; ellipses; ellipsoids; energy minimization problem; feature extraction; forest resources; geometric features; marked point processes; natural resource management; satellite images; stochastic geometry; tree position; vegetation resource parameter assessment; Biodiversity; Biological system modeling; Data mining; Geometry; Humans; Image resolution; Resource management; Satellites; Stochastic processes; Vegetation mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
ISSN :
1051-4651
Print_ISBN :
0-7695-2521-0
Type :
conf
DOI :
10.1109/ICPR.2006.20
Filename :
1698819
Link To Document :
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