A Distributed K-Means Segmentation Algorithm Applied to Lobesia botrana Recognition

Abstract EN

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.