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A Novel Method for 3D Image Segmentation with Fusion of Two Images using Color K-means Algorithm
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 123 - Number 4 |
| Year of Publication: 2015 |
| Authors: Neelam Kushwah, Priusha Narwariya |
10.5120/ijca2015905254
|
Neelam Kushwah, Priusha Narwariya . A Novel Method for 3D Image Segmentation with Fusion of Two Images using Color K-means Algorithm. International Journal of Computer Applications. 123, 4 ( August 2015), 10-14. DOI=10.5120/ijca2015905254
Abstract
In this proposed paper presented 3D image segmentation and fusion of two images using color automatic k-means clustering algorithm. It is a low level operation concerned with separating of images using calculating similarity or discontinuity, or homogeneously, by finding edges or boundaries’. Image segmentation is the process of splitting an image into several partitions, so as to change the optimization of an image into somewhat that is more expressive and easier to analyze. The experimental results give better results in terms of normalized cross correlation, absolute error and execution time. It gives improved results as compared to level set segmentation method.
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