Volume & Issue no: Volume 4, Issue 4, July - August 2015
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Title: |
PERFORMANCE EVALUATION OF IMPROVED IMAGE SEGMENTATION USING FUZZY BASED MODIFIED MEAN SHIFT AND MST |
Author Name: |
Sandeep Kaur, Shikha Chawla |
Abstract: |
The quantity of segmentation is serious in supreme errands
challenging image analysis. The attainment or
disappointment of the assignment is often a straight
implication of the attainment or else disappointment of
division. However, a dependable besides exact division of an
image remains definite hard to achieve through decorously
instinctive properties. Segmentation is generally the major
stage in some determination to inspect an image regularly. All
segmentation methods consume its particular aids and
confines. No method is finest for all kind of images, certain
methods are finest appropriate aimed at low concentration
images, certain remain finest aimed at composite contextual
images. The modified mean shift and minimum spanning tree
based segmentation agonizes since numerous issues.
Specifically this method is not well appropriate for composite
contextual images. Consequently in directive toward decrease
this subject, this paper has focused on unsupervised object
based image segmentation, using a fuzzy based modified mean
shift (MS) and a minimum spanning tree (MST) based
clustering method of remotely sensed satellite images and at
last performance is evaluated using various parameters.
Keywords: Image segmentation, PSNR, MSE, Accuracy,
Efficiency |
Cite this article: |
Sandeep Kaur, Shikha Chawla , "
PERFORMANCE EVALUATION OF IMPROVED IMAGE SEGMENTATION USING FUZZY BASED MODIFIED MEAN SHIFT AND MST" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) ,
Volume 4, Issue 4, July - August 2015 , pp.
085-090 , ISSN 2278-6856.
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