Automatic Detection of Anatomical Features on 3D Ear Impressions for Canonical Representation

  • Sajjad Baloch
  • Rupen Melkisetoglu
  • Simon Flöry
  • Sergei Azernikov
  • Greg Slabaugh
  • Alexander Zouhar
  • Tong Fang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6363)

Abstract

We propose a shape descriptor for 3D ear impressions, derived from a comprehensive set of anatomical features. Motivated by hearing aid (HA) manufacturing, the selection of the anatomical features is carried out according to their uniqueness and importance in HA design. This leads to a canonical ear signature that is highly distinctive and potentially well suited for classification. First, the anatomical features are characterized into generic topological and geometric features, namely concavities, elbows, ridges, peaks, and bumps on the surface of the ear. Fast and robust algorithms are then developed for their detection. This indirect approach ensures the generality of the algorithms with potential applications in biomedicine, biometrics, and reverse engineering.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Sajjad Baloch
    • 1
  • Rupen Melkisetoglu
    • 1
  • Simon Flöry
    • 2
  • Sergei Azernikov
    • 1
  • Greg Slabaugh
    • 3
  • Alexander Zouhar
    • 1
  • Tong Fang
    • 1
  1. 1.Siemens Corporate ResearchPrincetonUSA
  2. 2.Vienna University of TechnologyWienAustria
  3. 3.Medicsight PLCLondonUK

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