An effective robust fingertip detection method for finger writing character recognition system

This paper proposes an effective and robust fingertip detection method in 2D plane and applies it to a novel vision based human computer interaction system: finger writing character recognition system (FWCRS). The fingertip detection approach consists of two stages. First, based on the grid sampling and the analysis of sampled hand contour, the fingertip was detected roughly. Then, the location of fingertip was localized precisely based on circle feature matching. Experiments suggest that the proposed fingertip detection method is capable of detecting fingertip in a reliable manner even in a complex background under different light conditions without any markers. To demonstrate the strength of the method, the method was run on 5 sequences with varying light condition, different degrees of clutter background and different speeds of finger movement, experiment shows that the correct rate can reach 98.5%. The finger writing character recognition system in this paper is particularly advantageous for human-computer interaction (HCI) in that users can communicate with computers by their favorite mean: handwriting. At the same time, they can perform handwriting with only their finger directly.