scholarly journals Spectral Methods in Image Segmentation: A Combined Approach

2005 ◽  
pp. 191-198 ◽  
Author(s):  
Fernando C. Monteiro ◽  
Aurélio C. Campilho
Keyword(s):  
Image Segmentation ◽  
Spectral Methods ◽  
Combined Approach

scholarly journals Segmentation of Blood cell Images using Hybrid K-means with Cluster Center Estimation Technique

2019 ◽  
Vol 8 (2S11) ◽  
pp. 160-163
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Medical Image ◽  
Medical Image Segmentation ◽  
Cluster Center ◽  
Estimation Technique ◽  
Combined Approach ◽  
Predominant Role ◽  
Cluster Number ◽  
Initial Cluster

Image segmentation plays a predominant role in the field of image processing. k- Means clustering is one of the most powerful algorithms for medical image segmentation. However, the randomly selected cluster number and initial centroids cause inconsistency in the image segmentation results. To overcome this limitation we have proposed a combined approach namely Hybrid K-Means with Cluster Center Estimation (HKMCCE) for image segmentation. The proposed technique use histogram peaks of the image to find the cluster number and initial cluster centers automatically.Moreover, it requires lessuser interaction to determine k-means initialization parameters. The performance of the proposed technique is compared with traditional segmentationmethods and it yields better results with less execution time.

scholarly journals Combined Approach for Image Segmentation

2014 ◽  
Vol 11 (3) ◽  
pp. 118-121
Author(s):  
Shradha Dakhare ◽  
◽  
Harshal Chowhan ◽  
Manoj B.Chandak
Keyword(s):  
Image Segmentation ◽  
Combined Approach

Finite volume and spectral methods applied to Pb-30%TI alloy solidification

2001 ◽  
Vol 11 (PR6) ◽  
pp. Pr6-151-Pr6-159 ◽  
Author(s):  
R. Guérin ◽  
M. El Ganaoui ◽  
P. Haldenwang ◽  
P. Bontoux
Keyword(s):  
Finite Volume ◽  
Spectral Methods ◽  
Ti Alloy ◽  
Alloy Solidification
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