Identification of plant species on large botanical image datasets
Authors: Naiara Aginako, Javier Lozano, Marco Quartulli, Basilio Sierra, Igor G. Olaizola
Date: 01.04.2014
Abstract
The continuously growing amount of multimedia content has enabled the application of image content retrieval solutions to different domains. Botanical scientists are working on the classification of plant species in order to infer the relevant knowledge that permits them going forward in their environmental researches. The manual annotation of the existing and newly creation plants datasets is an outsized task that is becoming more and more tedious with the daily incorporation of new images. In this paper we present an automatic system for the identification of plants based on not only the content of images but also on the metadata associated to them. The classification has been defined as a classification plus fusion solution, where the images representing different parts of a plant have been considered independently. The promising results bring to light the chances of the application computer vision solutions to botanical domain.
BIB_text
author = {Naiara Aginako, Javier Lozano, Marco Quartulli, Basilio Sierra, Igor G. Olaizola},
title = {Identification of plant species on large botanical image datasets},
keywds = {
Plant identification, Content retrieval, Image Classification, Image Processing, Probability Fusion
}
abstract = {
The continuously growing amount of multimedia content has enabled the application of image content retrieval solutions to different domains. Botanical scientists are working on the classification of plant species in order to infer the relevant knowledge that permits them going forward in their environmental researches. The manual annotation of the existing and newly creation plants datasets is an outsized task that is becoming more and more tedious with the daily incorporation of new images. In this paper we present an automatic system for the identification of plants based on not only the content of images but also on the metadata associated to them. The classification has been defined as a classification plus fusion solution, where the images representing different parts of a plant have been considered independently. The promising results bring to light the chances of the application computer vision solutions to botanical domain.
}
isbn = {978-1-4503-2782-4},
date = {2014-04-01},
year = {2014},
}
