INFORMATION RETRIEVAL FOR IMAGE MINING

Abstract

Many areas of commerce, government, academia, and hospitals create large collections of digital images. Through digitization of data and developments in technology it is very easy to acquire and store large quantities of data, mainly multimedia data. This data will be suitable to analyse in an efficient and fast manner by the different kinds of agencies of commercial to Military. Currently, tools for mining images are insufficient and require human involvement. Feature selection and extraction is the pre-processing step of Image Mining. Obviously this is a serious step in the whole scenario of Image Mining. Our method to mine from Images – to extract patterns and derive knowledge from large collections of images, deals chiefly with identification and extraction of unique features for a specific domain. Experimental results display that the features used are sufficient to identify the patterns from the Images. An interactive system was established which allows the user to define new features and to resolve unclear regions. This paper presented a new method for image retrieval using high level semantic features. It is based on extraction of low level colour, shape and texture features and their conversion into high level semantic features using fuzzy production rules, derived with the help of an image mining technique. Dempster-Shafer theory of evidence is applied to obtain a list of structures covering information for the image high level semantic features. Johannes Itten theory is helpful for obtaining high level colour features.

Authors and Affiliations

ShashiRekha. B, Dr. K. V. N. Sunitha

Keywords

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  • EP ID EP27943
  • DOI -
  • Views 205
  • Downloads 0

How To Cite

ShashiRekha. B, Dr. K. V. N. Sunitha (2014). INFORMATION RETRIEVAL FOR IMAGE MINING. International Journal of Research in Computer and Communication Technology, 3(6), -. https://europub.co.uk/articles/-A-27943