naa a22 4500 510727069 CHVBK 20180411082939.0 cr unu---uuuuu 180411e20130201xx s 000 0 eng 10.1007/s11947-011-0737-x doi (NATIONALLICENCE)springer-10.1007/s11947-011-0737-x Selection of Optimal Wavelength Features for Decay Detection in Citrus Fruit Using the ROC Curve and Neural Networks [Elektronische Daten] [Delia Lorente, Nuria Aleixos, Juan Gómez-Sanchis, Sergio Cubero, Jose Blasco] Early automatic detection of fungal infections in post-harvest citrus fruits is especially important for the citrus industry because only a few infected fruits can spread the infection to a whole batch during operations such as storage or exportation, thus causing great economic losses. Nowadays, this detection is carried out manually by trained workers illuminating the fruit with dangerous ultraviolet lighting. The use of hyperspectral imaging systems makes it possible to advance in the development of systems capable of carrying out this detection process automatically. However, these systems present the disadvantage of generating a huge amount of data, which must be selected in order to achieve a result that is useful to the sector. This work proposes a methodology to select features in multi-class classification problems using the receiver operating characteristic curve, in order to detect rottenness in citrus fruits by means of hyperspectral images. The classifier used is a multilayer perceptron, trained with a new learning algorithm called extreme learning machine. The results are obtained using images of mandarins with the pixels labelled in five different classes: two kinds of sound skin, two kinds of decay and scars. This method yields a reduced set of features and a classification success rate of around 89%. Springer Science+Business Media, LLC, 2011 Computer vision nationallicence Citrus fruits nationallicence Decay nationallicence Non-destructive inspection nationallicence Hyperspectral imaging nationallicence ROC curve nationallicence Lorente Delia Centro de Agroingeniería, Instituto Valenciano de Investigaciones Agrarias (IVIA), Cra. Moncada-Náquera km 5, 46113, Moncada, Valencia, Spain aut Aleixos Nuria Instituto Interuniversitario de Investigación en Bioingeniería y Tecnología Orientada al Ser Humano, Universitat Politècnica de València, Camino de Vera s/n, 46022, Valencia, Spain aut Gómez-Sanchis Juan Intelligent Data Analysis Laboratory, IDAL, Electronic Engineering Department, Universitat de València, Dr. Moliner 50, 46100, Burjassot, Valencia, Spain aut Cubero Sergio Centro de Agroingeniería, Instituto Valenciano de Investigaciones Agrarias (IVIA), Cra. Moncada-Náquera km 5, 46113, Moncada, Valencia, Spain aut Blasco Jose Centro de Agroingeniería, Instituto Valenciano de Investigaciones Agrarias (IVIA), Cra. Moncada-Náquera km 5, 46113, Moncada, Valencia, Spain aut Food and Bioprocess Technology Springer-Verlag 6/2(2013-02-01), 530-541 1935-5130 6:2<530 2013 6 11947 https://doi.org/10.1007/s11947-011-0737-x text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11947-011-0737-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Lorente Delia Centro de Agroingeniería, Instituto Valenciano de Investigaciones Agrarias (IVIA), Cra. Moncada-Náquera km 5, 46113, Moncada, Valencia, Spain aut NATIONALLICENCE 700 1- Aleixos Nuria Instituto Interuniversitario de Investigación en Bioingeniería y Tecnología Orientada al Ser Humano, Universitat Politècnica de València, Camino de Vera s/n, 46022, Valencia, Spain aut NATIONALLICENCE 700 1- Gómez-Sanchis Juan Intelligent Data Analysis Laboratory, IDAL, Electronic Engineering Department, Universitat de València, Dr. Moliner 50, 46100, Burjassot, Valencia, Spain aut NATIONALLICENCE 700 1- Cubero Sergio Centro de Agroingeniería, Instituto Valenciano de Investigaciones Agrarias (IVIA), Cra. Moncada-Náquera km 5, 46113, Moncada, Valencia, Spain aut NATIONALLICENCE 700 1- Blasco Jose Centro de Agroingeniería, Instituto Valenciano de Investigaciones Agrarias (IVIA), Cra. Moncada-Náquera km 5, 46113, Moncada, Valencia, Spain aut NATIONALLICENCE 773 0- Food and Bioprocess Technology Springer-Verlag 6/2(2013-02-01), 530-541 1935-5130 6:2<530 2013 6 11947 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer