Among the implementations of multi-touch technologies, computer vision is a widely used way to build the multi-touch table. The touch information are obtained through the processing the imaging of infrared lights which comes from the reflection on touching fingers. The processing includes finger area extraction, tracking, and rectification. Because of disturbance of environment and unequally spread of the infrared lights on the surface, the image processing methods of previous multi-touch toolkits have poor performance on the detection and tracking of touch fingers, and these methods have not considered the influence of finger moving and camera distortion. In this paper, we propose a multi-touch table toolkit named as MTDriver. In MTDriver, we use local extreme area to extract the possible areas of touch fingers, then we track the motion of touch fingers by the tracking method which use the adjacent frames information. Experiments show that MTDriver has higher precision, better performance, and more robust compared with the other toolkits.