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Data Mining-Based CBIR System

Data Mining-Based CBIR System
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Author(s): Shruti Kohli (Birla Institute of Technology, India)and Vijay Shankar Gupta (Birla Institute of Technology, India)
Copyright: 2016
Pages: 18
Source title: Biomedical Image Analysis and Mining Techniques for Improved Health Outcomes
Source Author(s)/Editor(s): Wahiba Ben Abdessalem KarĂ¢a (Taif University, Saudi Arabia & RIADI-GDL Laboratory, ENSI, Tunisia)and Nilanjan Dey (Department of Information Technology, Techno India College of Technology, Kolkata, India)
DOI: 10.4018/978-1-4666-8811-7.ch012

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Abstract

Multimedia mining primarily involves information analysis and retrieval based on implicit knowledge. The ever increasing digital image databases on the internet has created a need for using multimedia mining on these databases for effective and efficient retrieval of images. Contents of an image can be expressed in different features such as Shape, Texture and Intensity-distribution (STI). Content Based Image Retrieval (CBIR) is the efficient retrieval of relevant images from large databases based on features extracted from the image. The emergence and proliferation of social network sites such as Facebook, Twitter and LinkedIn and other multimedia networks such as Flickr has further accelerated the need of efficient CBIR systems. Analyzing this huge amount of multimedia data to discover useful knowledge is a challenging task. Most of the existing systems either concentrate on a single representation of all features or linear combination of these features. The need of the day is New Image Mining techniques need to be explored and a self-adaptable CBIR system needs to be developed.

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