- -

Optimised computer vision system for automatic pre-grading of citrus fruit in the field using a mobile platform

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Optimised computer vision system for automatic pre-grading of citrus fruit in the field using a mobile platform

Mostrar el registro sencillo del ítem

Ficheros en el ítem

Thumbnail
Nombre: Version-autor.pdf
Tamaño: 2.702Mb
Formato: PDF
Descripción: Versión del Autor.
Abrir
[Cerrado]
Nombre: SERGIO CUBERO ...
Tamaño: 640.1Kb
Formato: PDF
Descripción: Versión editorial
Solicitar una copia al autor
dc.contributor.author Cubero García, Sergio es_ES
dc.contributor.author Aleixos Borrás, María Nuria es_ES
dc.contributor.author Albert Gil, Francisco Eugenio es_ES
dc.contributor.author Torregrosa, A. es_ES
dc.contributor.author Ortiz Sánchez, María Coral es_ES
dc.contributor.author García Navarrete, Óscar Leonardo es_ES
dc.contributor.author Blasco Ivars, José es_ES
dc.date.accessioned 2017-02-06T12:03:08Z
dc.date.available 2017-02-06T12:03:08Z
dc.date.issued 2014-02
dc.identifier.issn 1385-2256
dc.identifier.uri http://hdl.handle.net/10251/77668
dc.description.abstract The mechanisation and automation of citrus harvesting is considered to be one of the best options to reduce production costs. Computer vision technology has been shown to be a useful tool for fresh fruit and vegetable inspection, and is currently used in post-harvest fruit and vegetable automated grading systems in packing houses. Although computer vision technology has been used in some harvesting robots, it is not commonly utilised in fruit grading during harvesting due to the difficulties involved in adapting it to field conditions. Carrying out fruit inspection before arrival at the packing lines could offer many advantages, such as having an accurate fruit assessment in order to decide among different fruit treatments or savings in the cost of transport and marketing non-commercial fruit. This work presents a computer vision system, mounted on a mobile platform where workers place the harvested fruits, that was specially designed for sorting fruit in the field. Due to the specific field conditions, an efficient and robust lighting system, very low-power image acquisition and processing hardware, and a reduced inspection chamber had to be developed. The equipment is capable of analysing fruit colour and size at a speed of eight fruits per second. The algorithms developed achieved prediction accuracy with an R-2 coefficient of 0.993 for size estimation and an R-2 coefficient of 0.918 for the colour index. es_ES
dc.description.sponsorship This research work has been funded by the Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria de Espana (INIA) and the European FEDER funds (projects RTA2009-00118-C02-01 and RTA2009-00118-C02-02). The authors wish to thank the collaboration of the company Argiles Diseny i Fabricacio, S.L. en_EN
dc.language Inglés es_ES
dc.publisher Springer Verlag es_ES
dc.relation.ispartof Precision Agriculture es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Assisted harvesting es_ES
dc.subject Mobile platform es_ES
dc.subject Machine vision es_ES
dc.subject Smart camera es_ES
dc.subject Fruit pre-grading es_ES
dc.subject Citrus fruits es_ES
dc.subject.classification INGENIERIA AGROFORESTAL es_ES
dc.subject.classification EXPRESION GRAFICA EN LA INGENIERIA es_ES
dc.title Optimised computer vision system for automatic pre-grading of citrus fruit in the field using a mobile platform es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s11119-013-9324-7
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//RTA2009-00118-C02-02/ES/Optimización de los parámetros que afectan al desprendimiento y recogida de frutos cítricos mediante procedimientos mecánicos/ / es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//RTA2009-00118-C02-01/ES/RTA2009-00118-C02-01/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Mecanización y Tecnología Agraria - Departament de Mecanització i Tecnologia Agrària es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural - Escola Tècnica Superior d'Enginyeria Agronòmica i del Medi Natural es_ES
dc.description.bibliographicCitation Cubero García, S.; Aleixos Borrás, MN.; Albert Gil, FE.; Torregrosa, A.; Ortiz Sánchez, MC.; García Navarrete, OL.; Blasco Ivars, J. (2014). Optimised computer vision system for automatic pre-grading of citrus fruit in the field using a mobile platform. Precision Agriculture. 15(1):80-94. doi:10.1007/s11119-013-9324-7 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi. org/10.1007/s11119-013-9324-7 es_ES
dc.description.upvformatpinicio 80 es_ES
dc.description.upvformatpfin 94 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 15 es_ES
dc.description.issue 1 es_ES
dc.relation.senia 246261 es_ES
dc.identifier.eissn 1573-1618
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria es_ES
dc.description.references Baeten, J., Donné, K., Boedrij, S., Beckers, W., & Claesen, E. (2008). Autonomous fruit picking machine: A robotic apple harvester. Springer Tracts in Advanced Robotics, 42, 531–539. es_ES
dc.description.references Blasco, J., Aleixos, N., Gómez-Sanchis, J., & Moltó, E. (2009a). Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features. Biosystems Engineering, 103, 137–145. es_ES
dc.description.references Blasco, J., Aleixos, N., Roger, J. M., Rabatel, G., & Moltó, E. (2002). Robotic weed control using machine vision. Biosystems Engineering, 83(2), 149–157. es_ES
dc.description.references Blasco, J., Cubero, S., Gómez-Sanchis, J., Mira, P., & Moltó, E. (2009b). Development of a machine for the automatic sorting of pomegranate (Punica granatum) arils based on computer vision. Journal of Food Engineering, 90, 27–34. es_ES
dc.description.references Chong, V. K., Monta, M., Ninomiya, K., Kondo, N., Namba, K., Terasaki, E., et al. (2008). Development of mobile eggplant grading robot for dynamic in-field variability sensing––manufacture of robot and performance test. Engineering in Agriculture, Environment and Food, 1(2), 68–76. es_ES
dc.description.references Coppock, G. E., & Jutras, P. J. (1960). Mechanizing citrus fruit harvesting. Transactions of the ASAE, 3(2), 130–132. es_ES
dc.description.references Cubero, S., Aleixos, N., Moltó, E., Gómez-Sanchis, J., & Blasco, J. (2011). Advances in machine vision applications for automatic inspection and quality evaluation of fruits and vegetables. Food and Bioprocess Technology, 4(4), 487–504. es_ES
dc.description.references Cubero, S., Moltó, E., Gutiérrez, A., Aleixos, N., García-Navarrete, O. L., Juste, F., et al. (2010). Real-time inspection of fruit on a mobile harvesting platform in field conditions using computer vision. Progress in Agricultural Engineering Science, 6, 1–16. es_ES
dc.description.references DOGV. (2006). Diari Oficial de la Comunitat Valenciana, 5346, 30321–30328. es_ES
dc.description.references Edan, Y., Rogozin, D., Flash, T., & Miles, G. E. (2000). Robotic melon harvesting. IEEE Transactions on Robotics and Automation, 16(6), 831–834. es_ES
dc.description.references Ehsani, M. R., Grift, T. E., Maja, J. M., & Zhong, D. (2009). Two fruit counting techniques for citrus mechanical harvesting machinery. Computers and Electronics in Agriculture, 65(2), 186–191. es_ES
dc.description.references Feng, G., Qixin, C., & Masateru, N. (2008). Fruit detachment and classification method for strawberry harvesting robot. International Journal of Advanced Robotic Systems, 5(1), 41–48. es_ES
dc.description.references Gómez-Sanchis, J., Gómez-Chova, L., Aleixos, N., Camps-Valls, G., Montesinos-Herrero, C., Moltó, E., et al. (2008). Hyperspectral system for early detection of rottenness caused by Penicillium digitatum in mandarins. Journal of Food Engineering, 89(1), 80–86. es_ES
dc.description.references HunterLab. (2008). Applications note, 8(9) http://www.hunterlab.com/appnotes/an08_96a.pdf . Accessed Nov 2012. es_ES
dc.description.references Jiménez-Cuesta, M.J., Cuquerella, J., & Martínez-Jávega, J.M. (1981). Determination of a color index for citrus fruit degreening. In: Proceedings of the International Society of Citriculture, Tokyo (Japan), vol. 2 (pp. 750–753). es_ES
dc.description.references Jutras, P.J., & Coppock, G.E. (1958). Mechanization of citrus fruit picking. Florida State Horticultural Society, 71, 201,204. es_ES
dc.description.references Kohno, Y., Kondo, N., Iida, M., Kurita, M., Shiigi, T., Ogawa, Y., et al. (2011). Development of a mobile grading machine for citrus fruit. Engineering in Agriculture, Environment and Food, 4(1), 7–11. es_ES
dc.description.references Kondo, N. (2009). Robotization in fruit grading system. Sensors and Instrumentation for Food Quality, 3, 81–87. es_ES
dc.description.references Lee, W. S., & Slaughter, D. C. (2004). Recognition of partially occluded plant leaves using a modified Watershed algorithm. Transactions of the ASAE, 47, 1269–1280. es_ES
dc.description.references Lee, W. S., Slaughter, D. C., & Giles, D. K. (1999). Robotic weed control system for tomatoes. Precision Agriculture, 1(1), 95–113. es_ES
dc.description.references Li, Z., Li, P., & Liu, J. (2011). Physical and mechanical properties of tomato fruits as related to robot harvesting. Journal of Food Engineering, 103(2), 170–178. es_ES
dc.description.references Lorente, D., Aleixos, N., Gómez-Sanchis, J., Cubero, S., García-Navarrete, O. L., & Blasco, J. (2012). Recent advances and applications of hyperspectral imaging for fruit and vegetable quality assessment. Food and Bioprocess Technology, 5(4), 1121–1142. es_ES
dc.description.references Mazzetto, F., Calcante, A., Mena, A., & Vercesi, A. (2010). Integration of optical and analogue sensors for monitoring canopy health and vigour in precision viticulture. Precision Agriculture, 11(6), 636–649. es_ES
dc.description.references McBratney, A., Whelan, B., Ancev, T., & Bouma, J. (2005). Future directions of precision agriculture. Precision Agriculture, 6(1), 7–23. es_ES
dc.description.references Mizushima, A., & Lu, R. (2011). Cost benefits analysis of in-field presorting for the apple industry. Applied Engineering in Agriculture, 27(1), 33–40. es_ES
dc.description.references Muscato, G., Prestifilippo, M., Abbate, N., & Rizzuto, I. (2005). A prototype of an orange picking robot: Past history and experimental results. Industrial Robot, 32(2), 128–138. es_ES
dc.description.references Nieuwenhuizen, A. T., Hofstee, J. W., & van Henten, E. J. (2010). Adaptive detection of volunteer potato plants in sugar beet fields. Precision Agriculture, 11, 433–447. es_ES
dc.description.references Official Journal of European Communities. (2001). 14.09.2001. pp. L244/12–L244/18. http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2001:244:0012:0018:EN:PDF . Accessed May 2013. es_ES
dc.description.references Ortiz, C., Blasco, J., Balasch, S., & Torregrosa, A. (2011). Shock absorbing surfaces for collecting fruit during the mechanical harvesting of citrus. Biosystems Engineering, 110, 2–9. es_ES
dc.description.references Qiao, J., Sasao, A., Shibusawa, S., Kondo, N., & Morimoto, E. (2004). Mobile fruit grading robot (part1)––Development of a robotic system for grading sweet peppers. Journal of the Japanese Society of Agricultural Machinery (JSAM), 66(2), 113–122. es_ES
dc.description.references Qiao, J., Sasao, A., Shibusawa, S., Kondo, N., & Morimoto, E. (2005). Mapping yield and quality using the mobile fruit grading robot. Biosystems Engineering, 90(2), 135–142. es_ES
dc.description.references Ruiz-Altisent, M., Ortiz-Cañavate, J., & Valero, C. (2004). Fruit and vegetables harvesting systems. In: R. Dris and S. M. Jain (Eds.), Production practices and quality assessment of food crops, vol. 1: Preharvest practice (pp. 261–285). Dordrecht: Kluwer. es_ES
dc.description.references Torregrosa, A., Gil, J., Ortiz, C., Ortí, E., & Martín, B. (2009). Mechanical harvesting of oranges and mandarins in Spain. Biosystems Engineering, 104(1), 18–24. es_ES
dc.description.references Vidal, A., Talens, P., Prats-Montalbán, J. M., Cubero, S., Albert, F., & Blasco, J. (2012). In-line estimation of the standard colour index of citrus fruits using a computer vision system developed for a mobile platform. Food and Bioprocess Technology,. doi: 10.1007/s11947-012-1015-2 . es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem