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

المؤلفون المشاركون

García, José
Altimiras, Francisco
Pope, Christopher

المصدر

Complexity

العدد

المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-14، 14ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2017-08-09

دولة النشر

مصر

عدد الصفحات

14

التخصصات الرئيسية

الفلسفة

الملخص 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.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

García, José& Pope, Christopher& Altimiras, Francisco. 2017. A Distributed K-Means Segmentation Algorithm Applied to Lobesia botrana Recognition. Complexity،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1143013

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

García, José…[et al.]. A Distributed K-Means Segmentation Algorithm Applied to Lobesia botrana Recognition. Complexity No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1143013

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

García, José& Pope, Christopher& Altimiras, Francisco. A Distributed K-Means Segmentation Algorithm Applied to Lobesia botrana Recognition. Complexity. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1143013

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1143013