Time series case based reasoning for image categorisation

Ashraf Elsayed, and Mohd Hanafi Ahmad Hijazi, and Coenen, Frans P. and García-Fiñana, Marta and Sluming, Vanessa A. and Zheng, Yalin (2011) Time series case based reasoning for image categorisation. In: 19th International Conference on Case-Based Reasoning, ICCBR 2011, 12-15 September 2011, London.

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Official URL: http://dx.doi.org/10.1007/978-3-642-23291-6_31

Abstract

This paper describes an approach to Case Based Reasoning (CBR) for image categorisation. The technique is founded on a time series analysis mechanism whereby images are represented as time series (curves) and compared using time series similarity techniques. There are a number of ways in which images can be represented as time series, this paper explores two. The first considers the entire image whereby the image is represented as a sequence of histograms. The second considers a particular feature (region of interest) contained across an image collection, which can then be represented as a time series. The proposed techniques then use dynamic time warping to compare image curves contained in a case base with that representing a new image example. The focus for the work described is two medical applications: (i) retinal image screening for Age-related Macular Degeneration (AMD) and (ii) the classification of Magnetic Resonance Imaging (MRI) brain scans according to the nature of the corpus callosum, a particular tissue feature that appears in such images. The proposed technique is described in detail together with a full evaluation in terms of the two applications.

Item Type:Conference Paper (UNSPECIFIED)
Uncontrolled Keywords:Case based reasoning, Dynamic time warping, Image analysis, Time series analysis
Subjects:Q Science > QA Mathematics > QA76 Computer software
Divisions:SCHOOL > School of Engineering and Information Technology
ID Code:3699
Deposited By:IR Admin
Deposited On:12 Jul 2012 16:37
Last Modified:30 Dec 2014 09:36

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