• DocumentCode
    2628812
  • Title

    EigenNail for Finger Force Direction Recognition

  • Author

    Sun, Yu ; Hollerbach, John M. ; Mascaro, Stephen A.

  • Author_Institution
    Sch. of Comput., Utah Univ., Salt Lake, UT
  • fYear
    2007
  • fDate
    10-14 April 2007
  • Firstpage
    3251
  • Lastpage
    3256
  • Abstract
    This paper presents a technique termed eigennails to classify fingertip force during contact based on the coloration patterns in the fingernail and surrounding skin. Fingertip force is classified into six directions: no force, normal force only, two directions (left/right) of lateral shear force, and two directions (forward/backward) of longitudinal shear forces. Based on the face recognition technique eigenfaces, a small number of eigennails are sufficient to express the color pattern features for shear force direction classification. Results show that 98% of 960 fingernail images of 8 different subjects are correctly classified. The lowest imaging resolution without sacrificing classification accuracy is found to be 10-by-10.
  • Keywords
    eigenvalues and eigenfunctions; image colour analysis; image recognition; principal component analysis; coloration patterns; eigenfaces; eigennail; face recognition; finger force direction recognition; fingertip force classification; principal component analysis; shear force direction classification; Cities and towns; Face recognition; Fingers; Force measurement; Force sensors; Pattern recognition; Photodetectors; Sensor arrays; Skin; Sun;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 2007 IEEE International Conference on
  • Conference_Location
    Roma
  • ISSN
    1050-4729
  • Print_ISBN
    1-4244-0601-3
  • Electronic_ISBN
    1050-4729
  • Type

    conf

  • DOI
    10.1109/ROBOT.2007.363974
  • Filename
    4209592