Colour Image Clustering using K-Means
K. Sneha Silvia, Y. Vamsidhar, G Sudhakar · 2011
With the advancement in image capturing device, the image data has been generated at high volume. If images are analyzed properly, they can give useful information to the users. Content based image retrieval retrieves images relevant to the user needs from the image databases on the basis of low-level visual features that can be derived from the images. Grouping images into meaningful categories to reveal useful information is a challenging and important problem. Block Truncation Coding is used to extract features for image dataset and K-Means clustering algorithm is conducted to group the image dataset into various clusters.