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dc.contributor.authorOrdońẽz, Carlosen_US
dc.contributor.authorOmiecinski, Edward Robert
dc.date.accessioned2005-06-17T17:49:41Z
dc.date.available2005-06-17T17:49:41Z
dc.date.issued1998en_US
dc.identifier.urihttp://hdl.handle.net/1853/6632
dc.description.abstractWe introduce a new focus for data mining, which is concerned with knowledge discovery in image databases. We expect all aspects of data mining to be relevant to image mining but in this first work we concentrate on the problem of finding associations. To that end, we present a data mining algorithm to find association rules in 2-dimensional color images. The algorithm has four major steps: feature extraction, object identification, auxiliary image creation and object mining. Our algorithm is general in that it does not rely on any type of domain knowledge. A synthetic image set containing geometric shapes was generated to test our initial algorithm implementation. Our experimental results show that image mining is feasible. We also suggest several directions for future work in this area.en_US
dc.format.extent303108 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.relation.ispartofseriesCC Technical Report; GIT-CC-98-12en_US
dc.subjectData mining
dc.subjectImage databases
dc.subjectAlgorithms
dc.titleImage Mining: A New Approach for Data Miningen_US
dc.typeTechnical Reporteng_US


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