A New Technique for Hand Gesture Recognition

Author

Stergiopoulou, E. ; Papamarkos, P.

Author_Institution

Dept. of Electr. & Comput. Eng., Democritus Univ. of Thrace, Xanthi, Greece

fYear

2006

Firstpage

2657

Lastpage

2660

Abstract

A new method for hand gesture recognition is proposed which is based on an innovative self-growing and self-organized neural gas (SGONG) network. Initially, the region of the hand is detected by using a color segmentation technique that depends on a skin-color distribution map. Then, the SGONG network is applied on the segmented hand so as to approach its topology. Based on the output grid of neurons, palm geometric characteristics are obtained which in accordance with powerful finger features allow the identification of the raised fingers. Finally, the hand gesture recognition is accomplished through a probability-based classification method.

Keywords

fingerprint identification; gesture recognition; image classification; image colour analysis; image segmentation; neural nets; probability; SGONG network; color segmentation; finger feature identification; hand gesture recognition; palm geometric characteristic; probability-based classification; self-organized neural gas network; skin-color distribution map; Application software; Chromium; Computer vision; Fingers; Hidden Markov models; Image analysis; Image recognition; Image segmentation; Neural networks; Skin; Image analysis; Image segmentation; Image shape analysis; Neural network application;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2006 IEEE International Conference on

Conference_Location

Atlanta, GA

ISSN

1522-4880

Print_ISBN

1-4244-0480-0

Type

conf

DOI

10.1109/ICIP.2006.313056

Filename

4107115