建筑群多连通直线模式的参数识别方法

巩现勇; 武芳; 钱海忠; 马克楠

doi:10.13203/j.whugis20120708

建筑群多连通直线模式的参数识别方法

¹ 信息工程大学地理空间信息学院,河南郑州,450052;² 地理信息工程国家重点实验室,陕西西安,710054

基金项目: 国家自然科学基金资助项目 (41171354,41101362,41171305)；河南省创新型科技人才队伍建设工程资助项目(104200510016)；地理信息工程国家重点实验室开放研究基金资助项目(SKLGIE2013-M-4-6)

详细信息

作者简介:
巩现勇,硕士生,研究方向为模式识别、自动制图综合和时空数据分析。

中图分类号: P208;P283.1
计量
- 文章访问数: 1219
- HTML全文浏览量: 60
- PDF下载量: 716
出版历程
- 收稿日期: 2012-12-10
- 修回日期: 2014-03-04
- 发布日期: 2014-03-04

The Parameter Discrimination Approach to Multi-connectedLinear Pattern Recognition in Building Groups

¹Institute of Geographical Spatial Information,Information Engineering University,Zhengzhou 450052,China;²State Key Laboratory of Geo-information Engineering,Xi’an 710054,China

Funds: The National Natural Science Foundation of China,Nos.41171354,41101362,41171305;the Innovative TechnologyTalents Team Construction Project of Henan Province,No.104200510016;Funded by State Key Laboratory of Geo-information Engi-neering,No.SKLGIE2013-M-4-6.

More Information

Author Bio:
GONG Xianyong,master,specializes in pattern recognition,automated cartography generalization and spatio-temporal dataanalysis.

摘要

摘要: 目的结合国内外对建筑群空间分布模式的研究,提出了建筑群多连通直线模式的参数判别识别方法。首先从其组织规律出发,从距离、方向、大小3方面提取直线模式的结构化参数;然后利用 Delaunay三角网构建建筑群的邻近关系,生成邻近图;考虑直线模式的直线性、紧凑性等,通过模拟直线模式识别的人工过程进行邻近图的同质性修剪,识别出多连通直线模式。实验表明,该方法能够识别出明显直线模式,且具有完备性,允许模式相交,更符合人类空间认知特点。
- 制图综合 /
- 建筑群 /
- 多连通直线模式 /
- 模式识别
Abstract: Objective Map patterns in building groups,as one of the essential foundations for cartographic gener-alization and multi-scale connection-relations,embodies the relationship of the material form of citiesto their social-economic functions.On the basis of related research at home and abroad,a multi-con-nected linear pattern is recognized taking advantage of parameter discrimination.With the analysis ofpattern organization laws,the structural parameters of linear patterns are characterized by distance,direction and size;then the neighborhood relationship was captured by proximity graph with the helpof a Delaunay triangulation;finally the multi-connected linear pattern is recognized by pruning theproximity graph,modeling the human processes.Experiments show that this approach is effective,feasible and practicable for multi-connected linear pattern recognition in agreement with cognitivecharacteristics.
- cartographic generalization /
- building groups /
- multi-connected linear pattern /
- pattern rec-ognition