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Content-Based Image Retrieval of Skin Lesions by Evolutionary Feature Synthesis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publicationAPPLICATIONS OF EVOLUTIONARY COMPUTATION, PT I, PROCEEDINGS
EditorsC DiChic, C Cotta, M Ebner, A Ekart, AI EsparciaAlcazar, CK Goh, JJ Merelo, F Neri, M Preuss, J Togelius, GN Yannakakis
Place of PublicationBERLIN
PublisherSpringer-Verlag GmbH
Pages312-319
Number of pages8
ISBN (Print)978-3-642-12238-5
DOIs
Publication statusPublished - 2010
EventEuropean Conference on the Applications of Evolutionary Computation - Istanbul
Duration: 7 Apr 20109 Apr 2010

Conference

ConferenceEuropean Conference on the Applications of Evolutionary Computation
CityIstanbul
Period7/04/109/04/10

Abstract

This paper gives an example of evolved features that improve image retrieval performance. A content-based image retrieval system for skin lesion images is presented. The aim is to support decision making by retrieving and displaying relevant past cases visually similar to the one under examination. Skin lesions of five common classes, including two non-melanoma cancer types, are used. Colour and texture features are extracted from lesions. Evolutionary algorithms are used to create composite features that optimise a similarity matching function. Experiments on our database of 533 images are performed and results are compared to those obtained using simple features. The use of the evolved composite features improves the precision by about 7%.

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