A computer vision approach based on endocarp features for the identification of olive cultivars

Author:

Satorres Martínez S.,Martínez Gila D.,Beyaz A.,Gómez Ortega J.,Gámez García J.

Funder

IFAPA

CARDIOLIVE

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference25 articles.

1. A method to construct fruit maturity color scales based on support machines for regression: application to olives and grape seeds;Avila;J. Food Eng.,2015

2. Classification tools in chemistry. Part 1: linear models. PLS-DA;Ballabio;Anal. Methods,2013

3. Bari, A., Martin, A., Boulouha, A., Gonzalez Andujar, J.L., 2003. Characterization and identification of olive genotypes using an image feature extraction approach. In: IX Conferencia Espanola de Biometria La Coruna, 2003, pp. 5–8.

4. Identification of olive cultivars using image processing techniques;Beyaz;Turk. J. Agric. For.,2016

5. Identification of some spanish olive cultivars using image processing techniques;Beyaz;Sci. Hortic.,2017

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