Title :
An effective robust fingertip detection method for finger writing character recognition system
Author :
Duan-Duan Yang ; Lian-Wen Jin ; Jun-Xun Yin
Author_Institution :
Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China
Abstract :
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.
Keywords :
computer vision; handwritten character recognition; human computer interaction; pattern matching; sampling methods; 2D plane; HCI; circle feature matching; finger writing character recognition system; grid sampling; robust fingertip detection method; sampled hand contour; vision based human computer interaction system; Artificial intelligence; Cameras; Character recognition; Fingers; Human computer interaction; Image segmentation; Intelligent systems; Robustness; Sampling methods; Writing; Fingertip detection; background; circle features; template matching;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527822