Authors:
Manuel Grand-Brochier
1
;
Antoine Vacavant
2
;
Robin Strand
3
;
Guillaume Cerutti
4
and
Laure Tougne
4
Affiliations:
1
University Lumiere Lyon 2, France
;
2
University d’Auvergne, France
;
3
Uppsala University, Sweden
;
4
LIRIS UMR5205 CNRS, France
Keyword(s):
Tree Leaves Segmentation, Comparative Study, Distance Map, Pre-processing Tools.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
;
Segmentation and Grouping
Abstract:
In this paper, we present a comparative study highlighting the improvements provided by pre-processing tools, such as input stroke or use of distance map for segmentation approaches. We propose in particular to highlight new methods for calculating distance map based on the prediction of changes in local color (published by G. Cerutti et al. in ReVeS Participation - Tree Species Classification Using Random Forests and Botanical Features. CLEF 2012). We study differents methods using thresholding, clustering, or even active contours,
tested for an issue of tree leaves extraction. The observation criteria, such as Dice index, SSIM or MAD for example, allow us to analyze the performance obtained by each approach and in particular those of the GAC method, which are better for this context.