Static Hand Gesture Recognition using Mon-vision Based Techniques

Abstract

This paper reports the experimental studies conducted for recognizing the hand based static gestures. Mono-vision based skin color segmentation techniques are used for segmenting the hand form a complex image sequence. The standard histogram features along with various geometrical features are extracted from the experimental context under uniform lighting conditions.  American sign Language based hand gestures corresponding to the digits, ten digits, i.e., zero-to nine are used for study. Radial basis function neural network are used for classification.

Key Words: gesture recognition, static gesture recognition, mono-vision