Force prediction by fingernail imaging using active appearance models

This paper investigates the effect of two different parameters on the registration and force prediction accuracy of using Active Appearance Models (AAM) to align fingernail images. First, the color channel used to form the AAM is varied between (1) an averaged grayscale image, (2) the red channel, (3) the green channel and (4) the blue channel. Second, the number of landmark points used to create the AAM is varied between 6 and 75. The color channel is found to have an effect on the registration accuracy and the force prediction error. The green, blue and grayscale images are approximately equivalent, while the red images have a larger error across all metrics used. The number of landmark points may be reduced to 25 with no significant effect on either the registration accuracy or the force prediction error, though further reduction has shown some effect. With this information, a simpler registration model can be used that requires fewer calculations.