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A Gravitational Model for Grayscale Texture Classification Applied to the pap-smear Database

  • Jarbas Joaci de Mesquita Sá Junior
  • André R. BackesEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9280)

Abstract

This paper presents the application of a novel and very discriminative texture analysis method based on a gravitational model to a relevant medical problem, which is to classify pap-smear cell images. For this purpose, the complexity descriptors Bouligand-Minkowski fractal dimension and lacunarity were employed to extract signatures from the gravitational collapsing process. The obtained result was compared to other texture analysis methods. Additionally, AUC measure performance was computed and compared to several LBP based descriptors presented in two recent papers. The performed comparisons demonstrate that texture analysis based on gravitational model is suitable for discriminating pap-smear images.

Keywords

pap-smear database Gravitational model Bouligand-Minkowski fractal dimension Lacunarity 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Jarbas Joaci de Mesquita Sá Junior
    • 1
  • André R. Backes
    • 2
    Email author
  1. 1.Departamento de Engenharia de ComputaçãoCampus de Sobral - Universidade Federal do CearáSobralBrasil
  2. 2.Faculdade de ComputaçãoUniversidade Federal de UberlândiaUberlândiaBrasil

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