A Distributed K-Means Segmentation Algorithm Applied to Lobesia botrana Recognition. (9th August 2017)

• Record Type: Journal Article
• Authors: García, José; Pope, Christopher; Altimiras, Francisco
• Other Names: Wu Jia Academic Editor.
• Is Part Of: Complexity. Volume 2017(2017)
• Publication Date: 2017-08-09
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2017/5137317
• Languages: English
• ISSNs: 1076-2787

Abstract

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.