A support vector machine as an estimator of mountain papaya ripeness using resonant frequency or frequency centroid

Mountain papaya fruits (Vasconcella pubescens) were tested for firmness with a nondestructive acoustic method for 14 days after harvest. The response of each fruit was analyzed with the Fourier transform to obtain a firmness index (FI) based on the second resonant frequency and with the Short Time F...

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Detalles Bibliográficos
Autores principales: Bro, Per Bjarne, Gaete-Eastman, Carlos, Fernández, Mario, Moya León, Alejandra, Rosenberger, Christophe, Laurent, Hélène
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2006
Materias:
Ciencias Informáticas
Fast Fourier transforms (FFT)
frecuencia
support vector machine (SVM)
frequency centroid (FC)
firmness index (FI)
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/23935
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-23935
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Fast Fourier transforms (FFT)
frecuencia
support vector machine (SVM)
frequency centroid (FC)
firmness index (FI)
spellingShingle Ciencias Informáticas
Fast Fourier transforms (FFT)
frecuencia
support vector machine (SVM)
frequency centroid (FC)
firmness index (FI)
Bro, Per Bjarne
Gaete-Eastman, Carlos
Fernández, Mario
Moya León, Alejandra
Rosenberger, Christophe
Laurent, Hélène
A support vector machine as an estimator of mountain papaya ripeness using resonant frequency or frequency centroid
topic_facet Ciencias Informáticas
Fast Fourier transforms (FFT)
frecuencia
support vector machine (SVM)
frequency centroid (FC)
firmness index (FI)
description Mountain papaya fruits (Vasconcella pubescens) were tested for firmness with a nondestructive acoustic method for 14 days after harvest. The response of each fruit was analyzed with the Fourier transform to obtain a firmness index (FI) based on the second resonant frequency and with the Short Time Fourier Transform (STFT) to obtain a spectrogram frequency centroid (FC) index. The indexes were processed with a support vector machine (SVM) learning procedure in which days since harvest was taken as the basic truth of ripeness which the measured indexes attempt to estimate. The analysis of the results demonstrate that different groupings of the days into classes to be estimated give widely varying recognition rates and that the best rates are obtained when the classes are delimited using prior knowledge.
format Objeto de conferencia
Objeto de conferencia
author Bro, Per Bjarne
Gaete-Eastman, Carlos
Fernández, Mario
Moya León, Alejandra
Rosenberger, Christophe
Laurent, Hélène
author_facet Bro, Per Bjarne
Gaete-Eastman, Carlos
Fernández, Mario
Moya León, Alejandra
Rosenberger, Christophe
Laurent, Hélène
author_sort Bro, Per Bjarne
title A support vector machine as an estimator of mountain papaya ripeness using resonant frequency or frequency centroid
title_short A support vector machine as an estimator of mountain papaya ripeness using resonant frequency or frequency centroid
title_full A support vector machine as an estimator of mountain papaya ripeness using resonant frequency or frequency centroid
title_fullStr A support vector machine as an estimator of mountain papaya ripeness using resonant frequency or frequency centroid
title_full_unstemmed A support vector machine as an estimator of mountain papaya ripeness using resonant frequency or frequency centroid
title_sort support vector machine as an estimator of mountain papaya ripeness using resonant frequency or frequency centroid
publishDate 2006
url http://sedici.unlp.edu.ar/handle/10915/23935
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