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Memorias de investigación
Capítulo de libro:
Feature Extraction on Vineyard by Gustafson Kessel FCM and K-means
Áreas de investigación
  • Ingenierías,
  • Ciencias de la computación y tecnología informática
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.
Edición del Libro
Editorial del Libro
IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
IEEE Mediterranean Electrotechnical Conference-MELECON
Título del Libro
16th IEEE Mediterranean Electrotechnical Conference
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Esta actividad pertenece a memorias de investigación
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