Hand Shape Recognition Using Distance Transform and Shape Decomposition

Hand shape is a natural and human-friendly interface for human-computer interaction. This paper proposes a real- time and 2D vision-based hand shape recognition method. The method is robust to hand pose changes because the hand pose is neutralized after recognizing a hand pose using distance transform, principal component analysis (PCA), and histogram analysis. Also, the context-based recognition method using shape decomposition can effectively recognize tiny changes of fingers. The method worked at 44.8 fps and had a recognition rate of 83% on average in the experiment with 800 images including 5 hand shapes and 16 hand poses.This research was supported by Ministry of Culture, Sports and Tourism (MCST) and Korea Creative Content Agency (KOCCA) in the Culture Technology (CT) Research & Development Program 2009 (3rd year)