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

  • Lucia Ballerini
  • Xiang Li
  • Robert B. Fisher
  • Ben Aldridge
  • Jonathan Rees
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6024)

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%.

Keywords

Genetic Programming Texture Feature Colour Space Basal Cell Carcinoma Image Retrieval 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Lucia Ballerini
    • 1
  • Xiang Li
    • 1
  • Robert B. Fisher
    • 1
  • Ben Aldridge
    • 2
  • Jonathan Rees
    • 2
  1. 1.School of InformaticsUniversity of EdinburghUK
  2. 2.DermatologyUniversity of EdinburghUK

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