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Multispectral images segmentation using new fuzzy cluster centroid modified
(Institute of Electrical and Electronics Engineers Inc., 2017)
The presence of outliers, noise, corrupt pieces of data and great quantity of samples in a multispectral image, makes the segmentation analysis work tedious. The fuzzy clustering approach, specially, is susceptible to ...
Clustering stability for automated color image segmentation
(Pergamon-Elsevier Science Ltd, 2017-11)
Clustering is a well-established technique for segmentation. However, clustering validation is rarely used for this purpose. In this work we adapt a clustering validation method, Clustering Stability (CS), to automatically ...
Multispectral images segmentation using fuzzy probabilistic local cluster for unsupervised clustering
(Institute of Electrical and Electronics Engineers Inc., 2018)
In Pattern Recognition there are many algorithms it try to solve the problem of grouping objects of the same type, this is called clustering, however the task of dividing these lies not only in the objective function, but ...
Fuzzy C-Means Clustering with Histogram based Cluster Selection for Skin Lesion Segmentation using Non-Dermoscopic Images
Purpose – Pre-screening of skin lesion for malignancy is highly demanded as melanoma being a life-threatening skin cancer due to unpaired DNA damage. In this paper, lesion segmentation based on Fuzzy C-Means clustering ...
AUTOMATIC SUBCORTICAL TISSUE SEGMENTATION OF MR IMAGES USING OPTIMUM-PATH FOREST CLUSTERING
(Ieee, 2011-01-01)
Automatic MR-image segmentation of brain tissues is an important issue in neuroimaging. For instance, it is a key methodological component of a popular technique denominated voxel-based morphometry (VBM), which quantifies ...
The clusters Abell 222 and Abell 223: a multi-wavelength view
(EDP SCIENCES S A, 2010)
Context. The Abell 222 and 223 clusters are located at an average redshift z similar to 0.21 and are separated by 0.26 deg. Signatures of mergers have been previously found in these clusters, both in X-rays and at optical ...
New aspects of the elastic net algorithm for cluster analysis
(SPRINGER LONDON LTD, 2011)
Learning to Classify Seismic Images with Deep Optimum-Path Forest
(Ieee, 2016-01-01)
Due to the lack of labeled information, clustering techniques have been paramount in the last years once more. In this paper, inspired by the deep learning phenomenon, we presented a multi-scale approach to obtain more ...
Embedded clusters in NGC 1808 central starburst - Near-infrared imaging and spectroscopy
(EDP SCIENCES S A, 2008-08)
Context. In the course of a mid-infrared imaging campaign of close-by active galaxies, we discovered the mid-infrared counterparts of bright compact radio sources in the central star-forming region of NGC 1808.
Aims. We ...
Automatic shadow segmentation in aerial color images
(2003-01-01)
A robust and efficient technique to segment shaded areas in aerial color images is presented here. This technique is based on the physical phenomenon of atmospheric dispersion of the sunlight most well known as the Rayleigh ...