Improving the Efficiency of Image Clustering using Modified Non Euclidean Distance Measures in Data Mining
Keywords:Data Mining, Image Mining, Kmeans, Fuzzy Kmeans, Euclidean Distance
The Image is very important for the real world to transfer the messagesÂ from any source to destination. So, these images are converted in to useful informationÂ using data mining techniques. In existing all the research papers using kmeans andÂ fuzzy k means with euclidean distance for image clustering. Here, each cluster needsÂ its own centric for cluster calculation and the euclidean distance calculate the distanceÂ between the points. In clustering this process of distance calculation did not giveÂ efficient result. For make this in to efficient, this research paper proposes the nonÂ Euclidean distance measures for distance calculation. Here, the logical points are usedÂ to find the cluster. The result shows that image clustering based on the modified nonÂ Euclidean distance and the performance shows the efficiency of non euclidean distance
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