Image Mining for Image Retrieval Using Hierarchical K-Means Algorithm

Abstract

— Increasing use of World Wide Web and communication channels like mobile networking has in-creased the number of images used throughout the world. Continuing advancements in both hardware and software coupled with higher and image processing and image vision tools, have made it possible to store huge amount of images. This increase in number of images and image databases has necessitated the need for image mining. The analysis and characterization of image data is a complex procedure involving several processing phases, such as data acquisition, preprocessing, segmentation, feature extraction and classification. The proper combination and parameterization of the utilized methods are heavily relying on the given image dataset and experiment type. Image mining deals with the extraction of implicit knowledge, image data rela-tionship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vi-sion, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. In this paper we present a review on image mining for image retrieval using hierarchical k-means algorithm.