Abstract
In this paper, we present our results to build an automatic gesture recognition system using different types of cameras to compare them in reference to their features for segmentation. Normally, the images of a mono color camera system are mostly used as input data in the research area of gesture recognition. In comparison to that, the analysis results of a stereo color camera and a thermal camera system are used to determine the advantages and disadvantages of these camera systems. With this basics, a real-time gesture recognition system is build to classify alphabets (A-Z) and numbers (0-9) with an average recognition rate of 98% using Hidden Markov Models (HMM).