中文摘要：

包装反的图象表示(NAIR ) 使用的非对称预先规定的一些的例子的一个序列建原型代表一幅图象。当显著地减少要求代表一幅图象在的例子时然而，与空铅树和线性空铅树相反， NAIR 在这些例子之中失去了明确的空格关系并且因此使一些成为了象要实现的周界计算 hard 那样的几何操作。在这篇论文，经度和纬度格子(L ² G ) ，能从 NAIR 恢复失去的空格关系的数据结构是首先介绍了，然后计算图象的周界的一个新奇算法由 NAIR 代表了被介绍。试验性的结果证明新算法节省了基于空铅树与那作比较的至少 90% 操作时间。

英文摘要：

The non-symmetry anti-packing image representation （NAIR） uses a sequence of the instances of some predefined prototypes to represent an image. While significantly reducing the instances required to represent an image in contrary to the quadtree and the linear quadtree, however, NAIR has lost the explicit space relationship among these instances and hence made some geometric operations such as perimeter computation hard to be implemented. In this paper, longitude and latitude grid （L^2G）, a data structure which can restore lost space relationship from the NAIR is first presented, and then a novel algorithm to compute the perimeters of the images represented by the NAIR is presented. The experimental results show that the new algorithm has saved at least 90% of the running time comparing with that based on the quadtree.