Color Image Clustering Using Block Truncation Algorithm

Free registration required

Executive Summary

With the advancement in image capturing device, the image data been generated at high volume. If images are analyzed properly, they can reveal useful information to the human users. Content based image retrieval address the problem of retrieving images relevant to the user needs from 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. Clustering is a data mining technique to group a set of unsupervised data based on the conceptual clustering principal: Maximizing the intraclass similarity and minimizing the interclass similarity.

  • Format: PDF
  • Size: 299.5 KB