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Quantifying Mean Shape and Variability of Footprints Using Mean Sets

  • J. Domingo
  • B. Nacher
  • E. de Ves
  • E. Alcantara
  • E. Diaz
  • G. Ayala
  • A. Page
Conference paper
Part of the Computational Imaging and Vision book series (CIVI, volume 30)

Abstract

This paper1 presents an application of several definitions of a mean set for use in footwear design. For a given size, footprint pressure images corresponding to different individuals constitute our raw data. Appropriate footwear design needs to have knowledge of some kind of typical footprint. Former methods based on contour relevant points are highly sensitive to contour noise; moreover, they lack repeatability because of the need for the intervention of human designers. The method proposed in this paper is based on using mean sets on the thresholded images of the pressure footprints. Three definitions are used, two of them from Vorob’ev and Baddeley-Molchanov and one morphological mean proposed by the authors. Results show that the use of mean sets improves previous methodologies in terms of robustness and repeatability.

Keywords

Mean set morphological mean footprint footwear design 

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References

  1. [1]
    A.J. Baddeley and I.S. Molchanov. Averaging of random sets based on their distance functions. Journal of Mathematical Imaging and Vision, 8:79–92, 1998.CrossRefGoogle Scholar
  2. [2]
    A. Bataller, E. Alcántara, J.C. González, A.C. Garcia, and S. Alemany. Morphological grouping of Spanish feet using clustering techniques. In E. Hennig and H. Stacoff, A. and Gerber, editors, Proceedings of Fifth Symposium on Footwear Biomechanics, pages 12–13, 2001.Google Scholar
  3. [3]
    P.R. Cavanagh and M.M. Rodgers. The arch index: a useful measure from footprints. Journal of Biomechanics, 20(5):547–551, 1987.CrossRefPubMedGoogle Scholar
  4. [4]
    G.S. Daniels. The average man? Technical Note WCRD 53-7, Wright Air Development Center, Wrigth-Patterson Air Force Base, Dayton, Ohio, 1952.Google Scholar
  5. [5]
    E.C.F. Goonetilleke, R. S. Ho and R. H. Y. So. Foot anthropometry in Hong Kong. In Proceedings of the ASEAN 97 Conference, pages 81–98, 1997.Google Scholar
  6. [6]
    M.R. Hawes, R. Heinemeyer, D. Sovak, and B. Tory. An approach to averaging digitized plantagrams curves. Ergonomics, 37(7):1227–1230, 1994.PubMedGoogle Scholar
  7. [7]
    M.R. Hawes and D. Sovak. Quantitative morphology of the human foot in a North American population. Ergonomics, 37(7):1213–1226, 1993.Google Scholar
  8. [8]
    M.R. Hawes, D. Sovak, M Miyashita, S.J. Kang, Y. Yoshihuku, and S. Tanaka. Ethnic differences in forefoot shape and the determination of shoe comfort. Ergonomics, 37(1):187–193, 1994.PubMedGoogle Scholar
  9. [9]
    M. Kouchi and E. Tsutsumi. Relation between the medial axis of the foot outlina and 3-d foot shape. Ergonomics, 39(6):853–861, 1996.Google Scholar
  10. [10]
    P.E. Lestrel. Morphometricsfor the life sciences. World Scientific Press, 2000.Google Scholar
  11. [11]
    T. Lewis, R. Owens, and A. Baddeley. Averaging feature maps. Pattern Recognition, 32:1615–1630, 1999.CrossRefGoogle Scholar
  12. [12]
    W. Liu, J. Miller, D. Stefanyshyn, and B.N. Nigg. Accuracy and reliability of a technique for quantifying foot shape, dimensions and structural characteristics. Ergonomics, 42(2):346–358, 1999.CrossRefGoogle Scholar
  13. [13]
    A. Luximon, R.S. Goonetikelle, and K.L. Tsu. Foot landmarking for footwear customization. Ergonomics, 46(4):364–383, 2003.CrossRefPubMedGoogle Scholar
  14. [14]
    G. Matheron. Random sets and Integral Geometry. Wiley, London, 1975.Google Scholar
  15. [15]
    S. Pheasant. Bodyspace. Anthropometry, Ergonomics and Design. Taylor and Francis, London, 1986.Google Scholar
  16. [16]
    Wunderlich R.E. and Cavanagh PR. Gender differences in adult foot shape: Implications for shoe design. Medicine and Science in Sports & Exercise, 33(4):605–611, 2000.Google Scholar
  17. [17]
    C. Sforza, G. Michielon, N. Frangnito, and V.F Ferrario. Foot asymmetry in healthy adults: Elliptic fourier analysis of standardized footprints. Journal of Orthopaedic Research, 16(6):758–765, 1998.CrossRefPubMedGoogle Scholar
  18. [18]
    A. Simó, E. de Ves, G. Ayala, and J. Domingo. Resuming shapes with applications. Journal of Mathematical Imaging and Vision, 20:209–222, 2004.CrossRefMathSciNetGoogle Scholar
  19. [19]
    D. Stoyan and H. Stoyan. Fractals, Random Shapes and Point Fields. Methods of Geometrical Statistics. Wiley, 1994.Google Scholar
  20. [20]
    B.Y.S. Tsung, M. Zang, Y.B. Fan, and D.A. Boone. Quantitative comparison of platar foot shapes under different wheight-bearing conditions. Journal of Rehabilitation Research and Development, 40(6):517–526, 2003.PubMedGoogle Scholar
  21. [21]
    R.S. Urry and S.C. Wearing. A comparison of footprint indexes calculated form ink and electronic footprints. Journal of American Podiatric Medical Association, 91(4):203–209, 2001.Google Scholar

Copyright information

© Springer 2005

Authors and Affiliations

  • J. Domingo
    • 1
  • B. Nacher
    • 2
  • E. de Ves
    • 3
  • E. Alcantara
    • 2
  • E. Diaz
    • 3
  • G. Ayala
    • 4
  • A. Page
    • 2
  1. 1.Instituto de RoboticaUniversidad de ValenciaValenciaSpain
  2. 2.Institute de BiomecanicaUniversidad Politecnica de ValenciaValenciaSpain
  3. 3.Departamento de InformaticaUniversidad de ValenciaBurjasotSpain
  4. 4.Departamento de Estadistica e IOUniversidad de ValenciaBurjasotSpain

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