Paper Info
Title
Grassland species characterization for plant family discrimination by image processing
Abstract
Pasture species belonging to poaceae and fabaceae families constitute of essential elements to maintain natural and cultivated regions. Their balance and productivity are key factors for good functioning of the grassland ecosystems. The study is based on a process of image processing. First of all an individual signature is defined while considering geometric characteristics of each family. Then, this signature is used to discriminate between these families. Our approach focuses on the use of shape features in different situations. Specifically, the approach is based on cutting the representative leaves of each plant family. After cutting, we obtain leaves sections of different sizes and random geometry. Then, the shape features are calculated. Principal component analysis is used to select the most discriminatory features. The results will be used to optimize the acquisition conditions. We have a discrimination rate of more than 90% for the experiments carried out in a controlled environment. Experiments are being carried out to extend this study in natural environments.
Year
DOI
Venue
2010
10.1007/978-3-642-13681-8_21
ICISP
Keywords
Field
DocType
shape feature,grassland species characterization,natural environment,acquisition condition,different size,plant family,controlled environment,individual signature,plant family discrimination,different situation,image processing,fabaceae family,leaves section,principal component analysis,plant classification
Fabaceae,Pattern recognition,Poaceae,Computer science,Plant taxonomy,Image processing,Grassland,Pasture,Artificial intelligence,Principal component analysis,Ecosystem
Conference
Volume
ISSN
ISBN
6134
0302-9743
3-642-13680-X
Citations 
PageRank 
References 
1
0.37
10
Authors
5
Name
Order
Citations
PageRank
Mohamed Abadi192.36
Anne-Sophie Capelle-Laizé210.37
Majdi Khoudeir3103.32
Didier Combes410.37
Serge Carré510.37