Title

EigenNail for Finger Force Direction Recognition

Document Type

Conference Proceeding

Publication Date

4-2007

Keywords

principal component analysis, eigenvalues and eigenfunctions, image colour analysis, image recognition, principal component analysis, eigennail, finger force direction recognition, fingertip force classification, coloration patterns, face recognition, eigenfaces, shear force direction classification

Digital Object Identifier (DOI)

https://doi.org/10.1109/ROBOT.2007.363974

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.

Was this content written or created while at USF?

No

Citation / Publisher Attribution

Proceedings 2007 IEEE International Conference on Robotics and Automation, Roma, 2007, p. 3251-3256.