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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Approach Space Framework for Image Database Classification
verfasst von : Sheela Ramanna, James F. Peters
Erschienen in: Integrated Computing Technology
Verlag: Springer Berlin Heidelberg
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This article considers the problem of how to formulate a framework for classifying digital images in large-scale image databases. The solution to this problem stems from recent work on near tolerance rough sets and from the realisation that collections of images can be viewed in the context of approach spaces. A nonempty set equipped with a distance function satisfying certain conditions is an example of an approach space. In approach spaces, the notion of distance is closely related to the notion of nearness. Approach merotopies provide a means of determining the similarity between a query image and a collection of images. An application of approach space-based image classification is given in terms of collections of hand-finger movement images captured during therapeutic gaming system exercises.