[Imageworld] One year post-doc position: Comparison of segmentation
texture analysis for leaf images adapted to smartphones
antoine.vacavant at iut.u-clermont1.fr
Fri Mar 9 08:49:35 CET 2012
please consider the following pot-doc position, that should start by
September or October 2012.
Comparison of segmentation algorithms and texture analysis for leaf
images adapted to smartphones
Image segmentation; embedded image processing; evaluation of
segmentation algorithms; texture analysis; classification; multi-scale
Le Puy-en-Velay (43), France
Duration & salary:
12 months, starting at September or October 2012, paid approximately 1500€/month
ANR Project ReVeS (Reconnaissance de Végétaux pour des interfaces
Antoine Vacavant, antoine.vacavant at iut.u-clermont1.fr
Context & motivation:
The segmentation of natural images, such as plants in their
environment, is a very complex task and a challenge in many image
analysis applications. In the ReVeS project , we are interested in
the analysis of photos of tree leaves taken with a smartphone. The
main purpose of ReVeS is to propose an embedded application able to
recognize the tree associated with the processed leaf.
A first pipeline has been proposed in [2,3] in order to carry out this
process, keeping in mind that it should be embedded inside mobile
phones. Our approach tackles the problem of complex and uncontrolled
image background by using a model-based segmentation. We have shown
that classic segmentation algorithms like active contours, employed
without this a priori information, may lead to very noisy results, due
to the similarity between the object of interest and the background.
To ensure that our method leads to a high quality and competitive
result w.r.t. the literature, the main goal of this post-doc is to
study the comparison of segmentation algorithms, adapted to leaf
images and mobile phones.
First, the post-doc has to study the state of the art of segmentation
algorithms, and mainly (but not restricted to):
-multi-scale techniques (split & merge, multi-resolution, hierarchical, etc.);
-active contour or region growing methods (level sets, fast marching,
narrow band, etc.);
-clustering algorithms (k-means, etc.);
Simultaneously, a survey of evaluation criteria should be conducted,
and should also include:
covering area, by considering a binary mask as ground truth ;
-classification measures, as true/false positive/negatives,
F-measures, etc. as frequently used in background/foreground
segmentation algorithms in computer vision ;
-contour based criteria, by using the polygonal contour of the ground
truth, such as Haussdorff distance, error of tangents orientations,
The post-doc should implement many selected algorithms on a smartphone
or a tablet, to ensure the possibility to use them in a mobile
During this post-doc, the introduction of texture analysis -possibly
at several levels in a multi-scale scheme- should be studied to
improve the segmentation.
The use of texture could also be interesting for classification
issues, and could help to build a robust descriptor.
Besides knowledge on image/signal processing and algorithmic,
mathematics topics, the PhD should have good practice of C/C++ and or
Java programming (Java preferred). He/She would work with the DGtal
 and OpenCV libraries, and should have some basics on Android SDK
or an other SDK for mobile applications.
 ReVeS project (Reconnaissance de Végétaux pour des interfaces
 Guillaume Cerutti, Laure Tougne, Antoine Vacavant and Didier
Coquin. A Parametric Active Polygon for Leaf Segmentation and Shape
Estimation. In ISVC 2011, LNCS 6938, 202-213, 2011.
 Guillaume Cerutti, Laure Tougne, Julien Mille, Antoine Vacavant
and Didier Coquin. Guiding Active Contours for Tree Leaf Segmentation
and Identification. In CLEF 2011.
 Yoann Dhome, Nicolas Tronson, Antoine Vacavant, Thierry Chateau,
Christophe Gabard, Yann Goyat, and Dominique Gruyer. A Benchmark for
Background Subtraction Algorithms in Monocular Vision: a Comparative
Study. In IPTA 2010.
 Antoine Vacavant, Tristan Roussillon and Bertrand Kerautret.
Unsupervised Polygonal Reconstruction of Noisy Contours by a Discrete
Irregular Approach. In IWCIA 2011, LNCS 6636, pp. 389-409, 2011.
 DGtal (Discrete GeometryTools and Algorithms), http://liris.cnrs.fr/dgtal/.
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