A New Fingertip Detection Method Using the Top-Hat Transform

Abstract

This paper presents a new fingertip detection method that is based on the top-hat transform. A hand in an image is assumed to be segmented in advance. The palm of the hand is obtained using the morphological opening operation. Fingertips are then obtained as the opening residue, namely, the difference between the input image and the palm image. The performance of this approach is compared with three other techniques: (1) the convex hull algorithm, (2) the Kanade-Lucas-Tomasi (KLT) feature tracker, and (3) the SUSAN corner detector. Simulation results show that the method (1) is ineffective for closed hands. The methods (2) and (3) tend to respond falsely to many non-fingertip points. By contrast, the proposed method can detect fingertips with more than 90% success rates even for closed hands where the fingers are in contact with each other.

Keywords: Fingertip detection; Top-hat transform; Convex hull; KLT feature tracker; SUSAN corner detector.