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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Jumping Emerging Substrings in Image Classification
verfasst von : Łukasz Kobyliński, Krzysztof Walczak
Erschienen in: Computer Analysis of Images and Patterns
Verlag: Springer Berlin Heidelberg
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We propose a new image classification scheme based on the idea of mining jumping emerging substrings between classes of images represented by visual features. Jumping emerging substrings (JES) are string patterns, which occur frequently in one set of string data and are absent in another. By representing images in symbolic manner, according to their color and texture characteristics, we enable mining of JESs in sets of visual data and use mined patterns to create efficient and accurate classifiers. In this paper we describe our approach to image representation and provide experimental results of JES-based classification of well-known image datasets.