Gesture Recognition Algorithm using Morphological Analysis
Recently, research into computer, vision-based methods to recognize gestures are widely conducted as means to communicate the volition of humans to a computer. The most important problem of gesture recognition is a reduction in the simplification treatment time for algorithms by means of real-time treatment. In order to resolve this problem, this research applies mathematical morphology, which is based on geometric set theory. The orientations for the primitive shape elements of hand signal shapes acquired from the application of morphological shape analysis include important information on hand signals. Utilizing such a characteristic, this research is aimed at suggesting a feature vector-based, morphological gesture recognition algorithm from a straight line which connects central dots of major primitive shape elements and minor primitive shape elements. It will also demonstrate the usefulness of the algorithm by means of experimentation.
KeywordsHuman motion Computer vision
Funding of this paper was provided by Namseoul University.
- 1.Pavlovic VI, Sharma R, Huang TS (1997) Visual interpretation of hand gestures for human-computer interaction: a review. IEEE Trans. PAMI 19(7):677–695Google Scholar
- 2.Ahmad T, Taylor CJ, Lanitis A, Cootes TF (1997) Tracking and recognising hand gestures, using statistical shape models. Image Vis Comput 15:345–352, ElsevierGoogle Scholar
- 3.Wilson AD, Bobick AF (1999) Parametric hidden markov models for gesture recognition. IEEE Trans PAMI 21(9):884–900Google Scholar
- 4.Serra J (1986) Introduction to mathematical morphology. Comput Vis Graph Image Process 35(3):283–305Google Scholar
- 5.Serra J (1982) Image analysis and mathematical morphology. Academic Press, New YorkGoogle Scholar
- 6.Maragos P (1989) A representation theory for morphological image and signal processing. IEEE Trans Pattern Anal Mach Intell 11(6):586–599Google Scholar
- 7.Pitas I, Venesanopoulos AN (1990) Morphological shape decomposition. IEEE Trans Pattern Anal Mach Intell 12(1):38–45Google Scholar
- 8.Pitas I, Venetsanopoulos AN (1992) Morphological shape representation, Pattern Recog 25(6):555–565Google Scholar