NDLI: Wrapper-Based Feature Subset Selection for Rapid Image Information Mining

Content Provider	IEEE Xplore Digital Library
Author	Durbha, S.S. King, R.L. Younan, N.H.
Copyright Year	2004
Abstract	In a disaster, there is a need for rapid image-information retrieval in real or near real time from vast amounts of data coming from multiple remote-sensing sensors. In general, image information mining (IIM) approaches produce enormous amounts of features that are computationally expensive and inefficient to process before the actual information discovery takes place. Also, it is complicated because the combination of the features has little relevance to the hypothesis space. Hence, selecting a relevant subset of features is necessary to overcome these problems and to provide an efficient representation of the target class. In this letter, we propose feature selection and feature transformations based on a wrapper-based genetic algorithm approach. A support vector machine classification is applied for generating predictive models for those land-cover classes that are important in a coastal disaster event. The proposed system, rapid IIM, is a region-based approach where, in lieu of the prevalent pixel-based methods, it localizes interesting zones and enables rapid querying. Results from this study indicate that selecting relevant feature subsets increases the rate of correctly identifying a semantic class and also enables this process with less number of features.
Sponsorship	IEEE Geoscience and Remote Sensing Society
Starting Page	43
Ending Page	47
Page Count	5
File Size	699321
File Format	PDF
ISSN	1545598X
Volume Number	7
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Genetic algorithms Predictive models Image retrieval Image sensors Sea measurements Principal component analysis Senior members Information retrieval Support vector machine classification wrapper-based approaches Coastal disasters feature selection genetic algorithms (GAs) rapid image information mining (RIIM)
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Geotechnical Engineering and Engineering Geology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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