Content-based image retrieval of skin lesions by evolutionary feature synthesis

Authors:
Lucia Ballerini;Xiang Li;Robert B. Fisher;Ben Aldridge;Jonathan Rees
Affiliations:
School of Informatics, University of Edinburgh, UK;School of Informatics, University of Edinburgh, UK;School of Informatics, University of Edinburgh, UK;Dermatology, University of Edinburgh, UK;Dermatology, University of Edinburgh, UK
Venue:
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Year:
2010

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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%.