Abstract

The aim of this research is to build a robust image virtual input for robotic platform control. In this paper, we propose robust real-time hand gesture recognition input devices to control the robotic platform. hand gesture algorithm is built on two main steps: hand segmentation and gesture recognition. The hand segmentation is performed using skin colour as a detection cue. From the segmentation process, we extract the hand features that are required for the gesture recognition process. The fundamental model of the system is to control the robotic platform based on the number of active fingers counted from the gesture recognition process. A set of six instructions including stop, start, forward, backward, left and right is presented.

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