空间数据的不确定性将直接影响地理信息产品的质量有GIS空间决策的可靠性，现已把它作为一个重要的基础理论问题加以研究，其中线元的位置不确定性是研究的一个热点，针对现有的线元位置不确定性模型的不足，通过引入信息熵理论，首先提出了二维随机点的熵误差椭圆指标与三维随机点的熵误差椭球指标；然后将它们扩展到线元的熵不确定带，实践证明，由于该模型能够根据联合熵唯一确定，且与置信水平的选取无关，因此比较适合作为线元位置不确定性度量的指标。

With the development of the advanced techniques of human-computer interaction (HCI), gesture recognition is becoming one of the key techniques of HCI. Due to some notable advantages of vision-based gesture recognition(VGR), e.g. more naturalness to HCI, now VGR is an active research topic in the fields of image processing, pattern recognition, computer vision and others. The method of model matching using Hausdorff distance has the characters of low computing cost and strong adaptability. The system described in this paper applies the hausdorff distance for the first time to visually recognize the chinese finger alphabet(CFA) gestures (total 30 gestures) with the recognition features of edge pixels in the distance transform space. In order to improve the robust performance of the system, the modified hausdorff distance(MHD) has been proposed and applied in the recognition process. The average recognition rate of the system using MHD is up to 96.7% on the testing set. The experimental result of the system shows that using the method of model matching based on the Hausdorff distance to realize the vision-based static gesture recognition is feasible.