Sensors for fruit firmness assessment: Comparision and fusion

Steinmetz, V. and Crochon, M. and Bellon Maurel, V. and García Fernández, José Luis and Barreiro Elorza, Pilar and Verstreken, L. (1996). Sensors for fruit firmness assessment: Comparision and fusion. "Journal of Agricultural Engineering Research", v. 64 (n. 1); pp. 15-27. ISSN 0021-8634. https://doi.org/10.1006/jaer.1996.0042.

Description

Title: Sensors for fruit firmness assessment: Comparision and fusion
Author/s:
  • Steinmetz, V.
  • Crochon, M.
  • Bellon Maurel, V.
  • García Fernández, José Luis
  • Barreiro Elorza, Pilar
  • Verstreken, L.
Item Type: Article
Título de Revista/Publicación: Journal of Agricultural Engineering Research
Date: May 1996
ISSN: 0021-8634
Volume: 64
Subjects:
Faculty: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Department: Ingeniería Rural [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Non-destructive measurement of fruit firmness is a difficult problem and many different sensors have been developed in order to achieve this task. Three different European laboratories were associated in collaborative experiments on peaches, to compare three different sensing techniques, namely, sound, impact and micro-deformation. A Bayesian classifier is associated with each individual sensor and provides a classification into three categories, namely “soft”, “half firm” and “firm”. The fusion of the different sensors is performed by using Bayesian classifiers associated with heuristic methods for identity fusion. The result of the identity fusion is compared with the classification provided by an unsupervised algorithm based on destructive measurements. The fusion process provides some improvement in the classification results. For the individual sensors, the error rate of the classification varied from 19 to 28%, but the fusion process reduced this to 14%. Moreover, all measures of agreement between sensors lead to the conclusion that fusing sensors is better than using individual sensors

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