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object oriented gis semantic model
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  相似匹配句对
     OBJECT-ORIENTED AND ITS DEVELOPMENT
     面向对象及其发展
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     OBJECT-ORIENTED ANNEALING
     面向对象退火
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     object oriented GIS;
     面向对象的GIS;
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     Object-Oriented Blackboard Model
     面向对象的黑板模型
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     On Object-Oriented Visualization Model
     面向对象的可视化模型研究
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Semantics-based image retrieval research comes forth for filling the gap between images' low level vision features and users' high level semantics,and image's semantic description and extraction are its crucial problems.An approach of GIS semantics-based remote sensing image retrieval is proposed.This approach mainly includes two parts: the description of spatial features' semantics and semantic matching.Object-oriented GIS semantic model and conceptual semantic...

Semantics-based image retrieval research comes forth for filling the gap between images' low level vision features and users' high level semantics,and image's semantic description and extraction are its crucial problems.An approach of GIS semantics-based remote sensing image retrieval is proposed.This approach mainly includes two parts: the description of spatial features' semantics and semantic matching.Object-oriented GIS semantic model and conceptual semantic network are simultaneously applied to describe the spatial features' semantics.A semantic mediator is designed to process the semantic contradiction between user and system.The system will execute a group of atomic queries to get relevant results.Assembled through Boolean calculation,these results will afterward lead to vector GIS retrieval results.Based on vector query results,by reading the remote sensing image data which have the same coordinate frame with GIS data from areas determined by the minimum exterior rectangle obtained as the union of all vector polygons,final GISSBIR retrieval results shall be produced.This approach is applied to retrieve high resolution remote sensing image database,and the results are satisfied.

语义图像检索为填补图像低层视觉特征和用户高层语义之间的鸿沟而产生,图像语义描述和提取是其关键。提出了一种基于G IS语义的遥感图像检索(G IS sem antics-based remote sensing im age retrieval,简称G ISSB IR)方法,主要涉及空间对象的语义表达和语义匹配两方面内容。利用面向对象G IS语义模型和概念语义网络共同表达空间对象的语义,设计了语义调解器处理用户与系统之间的语义不一致。通过对G IS原子查询结果进行布尔运算得到矢量查询结果,在此基础上得到与G IS数据具有统一坐标框架的遥感图像检索结果。实验结果表明G ISSB IR方法是有效的。

 
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