Location Representation and Cardinal Direction Relation Reasoning Based on Qualitative Coordinates

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Location Representation and Cardinal Direction Relation Reasoning Based on Qualitative Coordinates

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- Location Representation and Cardinal Direction Relation Reasoning Based on Qualitative Coordinates
- Vol. 44, Issue 8, Pages: 36-41(2010)
- 作者机构：
  
  哈尔滨理工大学计算机科学与技术学院,哈尔滨,150080
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP311.13
- Online First：10 August 2010，
  
  Published：2010
- 稿件说明：
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Location Representation and Cardinal Direction Relation Reasoning Based on Qualitative Coordinates[J]. 2010, 44(8): 36-41.
DOI：

Location Representation and Cardinal Direction Relation Reasoning Based on Qualitative Coordinates[J]. 2010, 44(8): 36-41. DOI：

摘要

针对现有的位置关系表达模型均面向点对象

提出了定性直角坐标的概念

基于此概念提出了一种平面区域对象位置关系表达模型

该模型通过记录主对象与参考对象的定性位置区域的交集是否为空

由此构造位置矩阵来表达区域对象间的位置关系

从而较好地反映了对象的形状及对象间的空间布局

可有效地表达区域对象间的位置关系

并通过定性坐标将方向和距离关系有机地结合在一起形成统一的表达和推理模型.为了提高主方向关系推理的精度

基于该模型又提出了一个主方向关系推理算法

并对其正确性进行了验证.理论分析和实例验证的结果表明

该算法降低了推理的不确定性

提高了推理的精度.

Abstract

Since all the existing models for position relation concentrate on position between points

the concept of qualitative Cartesian rectangular coordinate is proposed and then a model based on the concept is presented for the position relations between regions. The model uses a position matrix to represent position relations. The position matrix records intersections among the qualitative position region of the primary object and the qualitative position regions of the reference objects. The model well reflects the shapes of objects and the spatial configurations among objects

and excellently represents position relations among regions. Direction and distance are effectively integrated by means of qualitative Cartesian rectangular coordinates to form a unified model for representation and reasoning. In order to improve the precision of reasoning with cardinal direction relation

an algorithm is proposed based on the proposed model and is shown to be correct in theory. The results of both theoretical analyzing and experiments show that the algorithm indeed improves the precision of reasoning.

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references

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FRANK A U. Qualitative spatial reasoning about distances and directions in geographic space [J]. Journal of Visual Languages and Computing, 1992(3):343-371.

HONG J H, EGENHOFER M J, FRANK A U. On the robustness of qualitative distance and directions reasoning[C]∥Proc of Auto-Carto 12. Charlotte, North Carolina, USA: ACM/ASPRS, 1995: 301-310.

CLEMENTINI E, DI FELICE P, HERNANDEZ D. Qualitative representation of positional information [J]. Artificial Intelligence, 1997, 95(2):317-356.

刘新,刘文宝,李成名,等.3维GIS中位置关系的定性描述与推理[J].测绘学报,2008, 37(4):495-500.

LIU Xin, LIU Wenbao, LI Chengming, et al. Qualitative representation and reasoning of positional relationships in 3D GIS [J]. Acta Geodaetica et Cartographica Sinica, 2008,37(4): 495-500.

SKIADOPOULOS S, KOUBARAKIS M. Composing cardinal direction relations [J]. Artificial Intelligence, 2004, 152: 143-171.

HERNANDEZ D, CLEMENTINI E, DI FELICE P. Qualitative distances [C]∥Proc of COSIT'95. Berlin: Springer-Verlag, 1995:45-57.

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