Clustering of Image Data Using K-Means and Fuzzy K-Means

Abstract: Clustering is a major technique used for grouping of numerical and image data in data mining and image processing applications. Clustering makes the job of image retrieval easy by finding the images as similar as given in the query image. The images are grouped together in some given number of clusters. Image data are grouped on the basis of some features such as color, texture, shape etc. contained in the images in the form of pixels. For the purpose of efficiency and better results image data are segmented before applying clustering. The technique used here is K-Means and Fuzzy K-Means which are very time saving and efficient.

Md. Khalid Imam Rahmani, Naina Pal and Kamiya Arora. “Clustering of Image Data Using K-Means and Fuzzy K-Means”. International Journal of Advanced Computer Science and Applications (IJACSA) 5.7 (2014). http://dx.doi.org/10.14569/IJACSA.2014.050724

@article{Rahmani2014,
title = {Clustering of Image Data Using K-Means and Fuzzy K-Means},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2014.050724},
url = {http://dx.doi.org/10.14569/IJACSA.2014.050724},
year = {2014},
publisher = {The Science and Information Organization},
volume = {5},
number = {7},
author = {Md. Khalid Imam Rahmani and Naina Pal and Kamiya Arora}
}