Calibration of hand structures is one of important steps to create an individualized three-dimensional hand model and estimate hand-pose. Because the hand structure is covered by the hand surface

the common cameras cannot directly get the hand structure

and people were required to participate in the calibration of hand structure

which cannot be completely processed by the computer. That makes the calibration complex and more time is needed. In order to acquire an automatic calibration of a hand structure

a set of image segmentation and enhancement techniques were used to find the link structure of the hand

based on the relationship of hand prints and joints in the individual's hand. The techniques of 3D modeling using multiple cameras

3D fitting

and the Particle Swarm Optimization algorithm were used to optimize the link structure of hand. Proved by the experiments

the calibration method proposed in this paper can successfully extract the structure of the hand

and each stage of the calibration process doesn't need people participating in. Comparing with the original method

the calibration method proposed in this paper is completed by the computer. As a result the calibration time is saved and errors are reduced.