Hand gesture recognition for Indian Sign Language

Author

Ghotkar, Archana S. ; Khatal, Rucha ; Khupase, Sanjana ; Asati, Surbhi ; Hadap, Mithila

Author_Institution

Dept. of Comput. Eng., Pune Inst. of Comput. Technol., Pune, India

fYear

2012

fDate

10-12 Jan. 2012

Firstpage

1

Lastpage

4

Abstract

In this paper, we introduce a hand gesture recognition system to recognize the alphabets of Indian Sign Language. In our proposed system there are 4 modules: real time hand tracking, hand segmentation, feature extraction and gesture recognition. Camshift method and Hue, Saturation, Intensity (HSV) color model are used for hand tracking and segmentation. For gesture recognition, Genetic Algorithm is used. We propose an easy-to-use and inexpensive approach to recognize single handed as well as double handed gestures accurately. This system can definitely help millions of deaf people to communicate with other normal people.

Keywords

feature extraction; genetic algorithms; gesture recognition; image colour analysis; image segmentation; object tracking; Indian sign language alphabet; camshift method; double handed gesture; feature extraction; genetic algorithm; hand gesture recognition; hand segmentation; hue-saturation-intensity color model; real time hand tracking; single handed gesture; Feature extraction; Genetic algorithms; Gesture recognition; Handicapped aids; Hidden Markov models; Image color analysis; Image segmentation; Double handed Gestures; Feature Extraction; Gesture Recognition; Hand Tracking; Indian Sign Language; Segmentation; Single handed Gestures;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Communication and Informatics (ICCCI), 2012 International Conference on

Conference_Location

Coimbatore

Print_ISBN

978-1-4577-1580-8

Type

conf

DOI

10.1109/ICCCI.2012.6158807

Filename

6158807