Image Mining

Friday, 25 October 2013

CAROTID ARTARY

Posted by Ashokkumar at 04:01 No comments:
Email ThisBlogThis!Share to XShare to FacebookShare to Pinterest
Newer Posts Home
Subscribe to: Posts (Atom)

Introduction to image mining

Discovering knowledge from data stored in typical alphanumeric databases, such as relational databases,has been the focal point of most of the work in database mining. However, with advances in secondaryand tertiary storage capacity, coupled with a relatively low storage cost, more and more non standard data (e.g., in the form of images) is being accumulated. This vast collection of image data can also be mined to discover new and valuable knowledge. The problem of image mining combines the areas of content-based image retrieval, image understanding, data mining and databases. To our knowledge, no other work has been done with regard to mining knowledge from a collection of images from a database perspective. An initial step towards tapping into the undiscovered wealth of knowledge from mining image-bases is the focus of this paper. This work can also be seen as a starting point for an as yet, unexplored area that that can provide enormous benefits.
Image mining has two main themes. The first is mining large collections of images and the second is the combined data mining of large collections of image and associated alphanumeric data. As of now we have concentrated on mining only images; but our algorithm can be extended in a straightforward manner to handle images and associated alphanumeric data. An example of the first case might involve a collection of weather satellite imagery of various cities in the United States that has been recorded over an extended
period of time. The data mining objective might be to find if there is some pattern that exists for an individual city (over time) or if there is some pattern that exists between different cities. An example of the second case might involve medical imagery and patient (alphanumeric data) records. To develop an accurate diagnosis or prognosis both image data (such as Xrays, SPECT, etc.) and patient data (such as weight, prior health conditions, family history, etc.) can be examined together to find interesting associations.

Blog Archive

  • ▼  2013 (2)
    • ►  November (1)
    • ▼  October (1)
      • CAROTID ARTARY

About Me

My photo
Ashokkumar
View my complete profile

search

Ethereal theme. Powered by Blogger.