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
Link To Document :
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