Gesture analysis by computer is an important part of the human computer interface (HCI) and a gesture analysis method was developed using a skin-color-based method to extract the area representing the hand in a single image with a distribution feature measurement designed to describe the hand shape in the images. A hidden Markov model (HMM) based method was used to analyze the temporal variation and segmentation of continuous operational gestures. Furthermore, a transition HMM was used to represent the period between gestures, so the method could segment continuous gestures and eliminate non-standard gestures. The system can analyze 2 frames per second, which is sufficient for real time analysis. Gesture analysis by computer is an important part of the human computer interface (HCI) and a gesture analysis method was developed using a skin-color-based method to extract the area representing the hand in a single image with a distribution feature measurement designed describe the hand shape in the images. A hidden Markov model (HMM) based method was used to analyze the temporal variation and segmentation of continuous operational gestures, so the method could segment segment continuous gestures and eliminate non-standard gestures. The system can analyze 2 frames per second, which is sufficient for real time analysis.