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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Image Mining: A Case for Clustering Shoe prints

Image Mining: A Case for Clustering Shoe prints
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Author(s): Wei Sun (Monash University, Australia), David Taniar (Monash University, Australia) and Torab Torabi (La Trobe University, Australia)
Copyright: 2009
Pages: 16
Source title: Database Technologies: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): John Erickson (University of Nebraska, Omaha, USA)
DOI: 10.4018/978-1-60566-058-5.ch094


View Image Mining: A Case for Clustering Shoe prints on the publisher's website for pricing and purchasing information.


Advances in image acquisition and storage technology have led to tremendous growth in very large and detailed image databases. These images, once analysed, can reveal useful information to our uses. The focus for image mining in this article is clustering of shoe prints. This study leads to the work in forensic data mining. In this article, we cluster selected shoe prints using k-means and expectation maximisation (EM). We analyse and compare the results of these two algorithms.

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