DocumentCode :
3449143
Title :
Segmentation of elevation images based on a morphology approach for agricultural clod detection
Author :
Chimi-Chiadjeu, O. ; Vannier, E. ; Dusseaux, Richard ; Taconet, O. ; Hegarat-Mascle, S.L.
Author_Institution :
LATMOS, Univ. de Versailles St Quentin, Guyancourt, France
fYear :
2012
fDate :
16-18 Oct. 2012
Firstpage :
701
Lastpage :
705
Abstract :
This study deals with the segmentation of altitude or elevation images, i.e. images of the distance (z-coordinate) between the surface or objects and the camera plane. Specifically to our soil science application, these images are acquired on agricultural surfaces in order to evaluate their roughness. The cloddy structure being a key factor to characterize soil roughness, the elevation image analysis aims at detecting and identifying the clods as accurately as possible. Now, rather than defining a new segmentation algorithm, we propose to transform the input data so as to take into account the different criteria characterizing the clod objects, namely the relative altitude and a function of the gradient norm. The proposed approach was validated on three agricultural surfaces (two synthetic and one real) and the results compared to those of an algorithm previously developed specifically for the clod identification problem.
Keywords :
agriculture; gradient methods; image segmentation; mathematical morphology; agricultural clod detection; agricultural surfaces; elevation image analysis; elevation images; gradient norm; morphology approach; new segmentation algorithm; relative altitude; soil science application; Image segmentation; Rough surfaces; Soil; Surface morphology; Surface roughness; Surface topography; Surface treatment; Depth image; agricultural soil; cloddiness; segmentation; watershed;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2012 5th International Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-0965-3
Type :
conf
DOI :
10.1109/CISP.2012.6469994
Filename :
6469994
Link To Document :
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