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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