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International Conference on Advanced Concepts for Intelligent Vision Systems

ACIVS 2015: Advanced Concepts for Intelligent Vision Systems pp 452–463Cite as

Tooth Segmentation Algorithm for Age Estimation

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9386))

Abstract

The estimation of age of adult subjects usually is based on age-related changes in skeleton. An interesting non invasive method, recently developed, involves teeth parameters achievable from peri-apical X-ray. Specifically, this procedure estimates age of adults through the changes of the tooth due to the apposition of secondary dentine, using pulp and tooth area as fundamental parameters. Aim of this study is to define an algorithm able to detect the boundary of the interested tooth in order to apply an automatic procedure for age estimation. The algorithm is based on classical segmentation methods as thresholding and shape analysis. Furthermore, our early results obtained on a small sample, are encouraging to proceed on this path.

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Author information

Authors and Affiliations

  1. Division of Mathematics, University of Camerino, 62032, Camerino, Mc, Italy

    Mauro Bacaloni & Pierluigi Maponi

  2. AgEstimation Project, University of Macerata, 62100, Macerata, Mc, Italy

    Roberto Cameriere

Authors
  1. Mauro Bacaloni
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  2. Pierluigi Maponi
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  3. Roberto Cameriere
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Corresponding author

Correspondence to Mauro Bacaloni .

Editor information

Editors and Affiliations

  1. Dipartimento di Matematica e Informatica, Università di Catania, Catania, Catania, Italy

    Sebastiano Battiato

  2. Arcueil CX, France

    Jacques Blanc-Talon

  3. Catania, Italy

    Giovanni Gallo

  4. Gent, Belgium

    Wilfried Philips

  5. CSIRO, Sydney, New South Wales, Australia

    Dan Popescu

  6. Vision Lab., University of Antwerp, Antwerpen, Belgium

    Paul Scheunders

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© 2015 Springer International Publishing Switzerland

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Bacaloni, M., Maponi, P., Cameriere, R. (2015). Tooth Segmentation Algorithm for Age Estimation. In: Battiato, S., Blanc-Talon, J., Gallo, G., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2015. Lecture Notes in Computer Science(), vol 9386. Springer, Cham. https://doi.org/10.1007/978-3-319-25903-1_39

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  • DOI: https://doi.org/10.1007/978-3-319-25903-1_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25902-4

  • Online ISBN: 978-3-319-25903-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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