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Proceedings Paper

A technique for mapping irregular-sized vectors applied to image collections
Author(s): Jonathan D. Edwards; John K. Riley; John P. Eakins
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Paper Abstract

This paper describes a strategy to visualise a data-set of multi-component feature vectors using multidimensional scaling (MDS). MDS is employed, instead of more commonly applied mapping techniques, as it can utilise arbitrary distance measures and hence can easily incorporate the non-linear distance metrics employed when matching multi-component vectors. To test this mapping approach, we have applied it to a data-set of two hundred and sixty eight images, segmented into multiple components each represented by a shape descriptor. The inter-image distances are measured using a series of simple non-location based image distance metrics. The maps are encouraging, with well clustered areas for duplicate or near duplicate trademarks. This gives a clear indication that MDS can be used for this type of visualisation task. However, the maps themselves also significantly highlight the inadequacies of the segmentation and matching phases. Particularly for the images with an overall impression that doesn’t correspond to the segmented parts, for example figure/ground reversal or macro texture.

Paper Details

Date Published: 23 June 2003
PDF: 9 pages
Proc. SPIE 5150, Visual Communications and Image Processing 2003, (23 June 2003); doi: 10.1117/12.503044
Show Author Affiliations
Jonathan D. Edwards, Univ. of Northumbria (United Kingdom)
John K. Riley, Univ. of Northumbria (United Kingdom)
John P. Eakins, Univ. of Northumbria (United Kingdom)


Published in SPIE Proceedings Vol. 5150:
Visual Communications and Image Processing 2003
Touradj Ebrahimi; Thomas Sikora, Editor(s)

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