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Volume 2017 (2017), Article ID 5137317, 14 pages
https://doi.org/10.1155/2017/5137317
Research Article

A Distributed -Means Segmentation Algorithm Applied to Lobesia botrana Recognition

1Telefonica Investigación y Desarrollo, Santiago, Chile
2Pontificia Universidad Católica de Valparaíso, 2362807 Valparaíso, Chile
3Faculty of Engineering and Sciences, Universidad Adolfo Ibañez, Santiago, Chile

Correspondence should be addressed to José García; moc.acinofelet@aicrag.oinotnaesoj

Received 1 May 2017; Accepted 4 July 2017; Published 9 August 2017

Academic Editor: Jia Wu

Copyright © 2017 José García et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Early detection of Lobesia botrana is a primary issue for a proper control of this insect considered as the major pest in grapevine. In this article, we propose a novel method for L. botrana recognition using image data mining based on clustering segmentation with descriptors which consider gray scale values and gradient in each segment. This system allows a 95 percent of L. botrana recognition in non-fully controlled lighting, zoom, and orientation environments. Our image capture application is currently implemented in a mobile application and subsequent segmentation processing is done in the cloud.