Feature Extraction on Vineyard by Gustafson Kessel FCM and K-means

Correa Farias, Christian; Valero Ubierna, Constantino; Barreiro Elorza, Pilar; Diago Santamaria, Maria Paz y Tardaguila Laso, Javier (2012). Feature Extraction on Vineyard by Gustafson Kessel FCM and K-means. En: "16th IEEE Mediterranean Electrotechnical Conference", 25/03/2012 - 28/03/2012, Medina Yasmine Hammamet, Túnez.

Descripción

Título: Feature Extraction on Vineyard by Gustafson Kessel FCM and K-means
Autor/es:
  • Correa Farias, Christian
  • Valero Ubierna, Constantino
  • Barreiro Elorza, Pilar
  • Diago Santamaria, Maria Paz
  • Tardaguila Laso, Javier
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 16th IEEE Mediterranean Electrotechnical Conference
Fechas del Evento: 25/03/2012 - 28/03/2012
Lugar del Evento: Medina Yasmine Hammamet, Túnez
Título del Libro: Proceedings of the 16th IEEE Mediterranean Electrotechnical Conference.
Fecha: 25 Marzo 2012
Materias:
Palabras Clave Informales: fuzzy, vineyard, clustering.
Escuela: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Departamento: Ingeniería Rural [hasta 2014]
Licencias Creative Commons: Ninguna

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Resumen

Image segmentation is a process by which an image is partitioned into regions with similar features. Many approaches have been proposed for color images segmentation, but Fuzzy C-Means has been widely used, because it has a good performance in a wide class of images. However, it is not adequate for noisy images and it takes longer runtimes, as compared to other method like K-means. For this reason, several methods have been proposed to improve these weaknesses. Methods like Fuzzy C-Means with Gustafson-Kessel algorithm (FCM-GK), which improve its performance against the noise, but increase significantly the runtime. In this paper we propose to use the centroids generated by GK-FCM algorithms as seeding for K-means algorithm in order to accelerate the runtime and improve the performance of K-means with random seeding. These segmentation techniques were applied to feature extraction on vineyard images. Segmented images were evaluated using several quality parameters such as the rate of correctly classified area and runtime.

Más información

ID de Registro: 10282
Identificador DC: http://oa.upm.es/10282/
Identificador OAI: oai:oa.upm.es:10282
URL Oficial: http://www.melecon2012.org/
Depositado por: Investigador en formación Christian Correa Farías
Depositado el: 13 Feb 2012 07:42
Ultima Modificación: 22 Sep 2014 10:43
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