Identification of plant species on large botanical image datasets

Autores: Naiara Aginako, Javier Lozano, Marco Quartulli, Basilio Sierra, Igor G. Olaizola

Fecha: 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

@Article {
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},
}
Vicomtech

Parque Científico y Tecnológico de Gipuzkoa,
Paseo Mikeletegi 57,
20009 Donostia / San Sebastián (España)

+(34) 943 309 230

Zorrotzaurreko Erribera 2, Deusto,
48014 Bilbao (España)

close overlay

Las cookies de publicidad comportamental son necesarias para cargar el contenido

Aceptar cookies de publicidad comportamental