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

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

Description

Title: Feature Extraction on Vineyard by Gustafson Kessel FCM and K-means
Author/s:
  • Correa Farias, Christian
  • Valero Ubierna, Constantino
  • Barreiro Elorza, Pilar
  • Diago Santamaria, Maria Paz
  • Tardaguila Laso, Javier
Item Type: Presentation at Congress or Conference (Article)
Event Title: 16th IEEE Mediterranean Electrotechnical Conference
Event Dates: 25/03/2012 - 28/03/2012
Event Location: Medina Yasmine Hammamet, Túnez
Title of Book: Proceedings of the 16th IEEE Mediterranean Electrotechnical Conference.
Date: 25 March 2012
Subjects:
Freetext Keywords: fuzzy, vineyard, clustering.
Faculty: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Department: Ingeniería Rural [hasta 2014]
Creative Commons Licenses: None

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Abstract

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.

More information

Item ID: 10282
DC Identifier: http://oa.upm.es/10282/
OAI Identifier: oai:oa.upm.es:10282
Official URL: http://www.melecon2012.org/
Deposited by: Investigador en formación Christian Correa Farías
Deposited on: 13 Feb 2012 07:42
Last Modified: 22 Sep 2014 10:43
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