Estimation of Object Elasticity by Capturing Fingernail Images During Haptic Palpation

In this study, we present a system that performs natural-touch-based elasticity estimation for an object by using a depth camera. To estimate elasticity, which is defined as an object's Young's modulus, a strain-stress curve is obtained from fingernail images during haptic palpation. From a color image, the proposed system detects a fingernail and extracts 10 feature values related to the contact force; then, it estimates the force using a multiple regression model. Deformation of the object was estimated from the finger's three-dimensional position obtained from both color and depth images. Then, a strain-stress curve was determined using the force and deformation data. Evaluation experiments were designed to obtain the strain-stress curves of five objects from 10 participants; then, the estimation performance was investigated. The results show that the reliable range of sensing was within Young's modulus values of 0.12-5.6 MPa and the precision of the measurement was 55 percent of the estimated elasticity.