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Performance Comparison of Cluster Number of K-Means Clustering Algorithm Using Mammographic Image
Abstract
Clustering is a process of grouping the data which are similar and dissimilar data among to other group. In this process apply different number of clusters on mammographic image. Clustering process is a part of image segmentation. In image segmentation process various types of method available but here K-Means clustering is use. In this paper, performance of different cluster number is based on simulation result. From this simulation result compare contrast, correlation, energy, and homogeneity. Also compare the time taken by different cluster.
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References
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