形状识别在地图综合中的应用研究
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摘要
形状分析和形状识别是地图综合的重要内容之一,地图综合中首先就需要对地理要素进行结构的识别,包括对要素的分布模式和形状特征进行分析,以便获取地理要素和现象的分布规律,制定综合的总体策略。其二,同一要素在不同尺度的表达中应保持形状的主体轮廓的一致性,这就需要在综合算法中顾及形状的保真问题。其三,在地图综合的结果评价中,形状相似性是其重要的指标。地图是现实世界的抽象反映,没有形状的一致性人们很难将地图中的要素与真实的地理要素建立对应关系。但形状识别属于认知领域的范畴,具有很强的主观性和不确定性,目前形状识别的成果多集中在模式识别领域,因而,如何在地图综合的领域进行形状的分析与识别既存在挑战性,又具有极大的现实意义。本文主要在以下几个方面作一些尝试：
(1)系统总结了支持形状识别的基础理论。从形状的定义及特点入手,介绍了认知心理学中有关模式识别的三种模型——模板匹配模型、原型匹配模型、特征匹配模型,阐述了人类对形状的认知规律。从计算机和信息科学的角度,介绍和总结了有关形状识别的方法、模型以及地图科学中要素表达的形状特点。
(2)阐述了地理要素中面状要素的形状特征参数以及形状相似性识别的模型。重点将傅立叶形状描述子和形状数模型纳入到矢量面状要素的形状相似性度量中；分析了傅立叶形状描述子在刻画不同形状图形时的拟合精度；设计了一套适合建筑物的、具有平移、缩放、旋转形状度量不变性的形状数的求解方法,研究了不同尺度的形状数对形状度量的影响。
(3)在认知心理学模式识别的原型匹配模型的启发下,提出了基于动态模板匹配的建筑物多边形的化简方法。从原型模板设计、动态模板生成、要素与模板的匹配、模板放样、以及化简成果的有效性探测等五个方面详细地介绍了基于动态模板匹配的建筑物化简模型的原理、操作流程,并用实验验证了这一方法的有效性。
(4)从线状要素的形状特征单元——弯曲入手,详述了弯曲的划分、弯曲形状的识别、层次结构；总结和归纳了线状要素的单一特征参数、组合特征参数以及各参数的几何意义。
(5)在探讨了线状要素形状二维性——弯曲性与方向性的基础上,运用BP神经网络系统将线状要素按其形状进行分类与分段,拟对不同形状的线状要素和线状要素子段采用不同的化简模型和参数。
(6)阐述了线状要素化简可能带来的三个损失——点位精度、拓扑一致性、形状相似性,并简要分析了这三者之间的关系。在线状要素形状相似性分析的基础上,分析了不同的线状要素化简模型在化简中对形状的影响,得出了Douglas-Peucker化简模型具有精度损失最小、形状保真度最高的结论。
As an important characteristic of spatial cognition and a cognition result of graphic structure, pattern and distributing condition, shape plays a significant role in map generalization. Structural recognition of geographical features is essential in map generalization, which includes the analysis in distributing pattern and shape characteristic. Therefore, map generalization overall strategy could be established on the basis of the acquired distributing rule of geographical features and phenomena.Secondly, whereas a feature should be kept shape similarity in multi-scale representation, shape fidelity takes priority in generalization algorithm. Thirdly, shape similarity is an important index in map generalization evaluation. As an aspect in the field of cognition, shape recognition carries subjectivity and uncertainty. Therefore, shape analysis and recognition in map generalization is challanging and practical as well. This dissertation focused on the following:
(1) Theoretical bases supporting shape recognition are systematically summarized. From the start of the definition of shape, the dissertation introduces three models about pattern recognition——template matching model, prototype matching model and feature matching model in a systematical way and expatiates on human's cognitive regularity to shape. From the angle of the science of computer and information, the method or model about shape recognition and characteristics of shape representation of features in cartography are introduced and summarized.
(2) The shape characteristic value of area feature in GIS and the model of calculating shape similarity distance are interpreted in detail. The Fourier shape descriptor and shape number to calculating similarity distance of shape are placed great emphasis.The convergence speed and descriptive accuracy are analyzed when the Fourier descriptor applied in describing different kinds of shape. The method to obtain shape number with three invariances which is proper to building is devised and that the shape number with different scale exists influence on shape description is researched.
(3) Under the elicitation of prototype matching model of pattern recognition in cognition psychology, the dissertation presents the method of simplification of building based on dynamic template matching. The theory and operational processing of the method are provided from the aspects of prototype template designing, dynamic template creating, template setting and detecting validity of simplification result. The method has been proved practical by data experiment.
(4) shape characteristic unit——bend of line feature and its shape characteristic parameters are analysed. The partition, hierarchy of bend of line feature are explained. Simple shape characteristic parameters and composite shape characteristic parameters and their geometrical meaning are summarized.
(5) On the basis of the research of two dimension attributes of shape of line feature, the line feature is devided into different classes and is partitioned into many segments which have same shape characteristics, and the segments are simplified through different simplification algorithms and simplification threshold.
(6) The dissertation expatiates on the possible losses as a result of the simplification of line feature——position accuracy, topology consistency and shape similarity. The relations among the above-mentioned losses are also presented. The shape deformation of different line simplification model is analysed and the conclusion is drawed that Douglas-peucker simplification model is the most proper in position accuracy and fidelity of shape.
(1)系统总结了支持形状识别的基础理论。从形状的定义及特点入手,介绍了认知心理学中有关模式识别的三种模型——模板匹配模型、原型匹配模型、特征匹配模型,阐述了人类对形状的认知规律。从计算机和信息科学的角度,介绍和总结了有关形状识别的方法、模型以及地图科学中要素表达的形状特点。
(2)阐述了地理要素中面状要素的形状特征参数以及形状相似性识别的模型。重点将傅立叶形状描述子和形状数模型纳入到矢量面状要素的形状相似性度量中；分析了傅立叶形状描述子在刻画不同形状图形时的拟合精度；设计了一套适合建筑物的、具有平移、缩放、旋转形状度量不变性的形状数的求解方法,研究了不同尺度的形状数对形状度量的影响。
(3)在认知心理学模式识别的原型匹配模型的启发下,提出了基于动态模板匹配的建筑物多边形的化简方法。从原型模板设计、动态模板生成、要素与模板的匹配、模板放样、以及化简成果的有效性探测等五个方面详细地介绍了基于动态模板匹配的建筑物化简模型的原理、操作流程,并用实验验证了这一方法的有效性。
(4)从线状要素的形状特征单元——弯曲入手,详述了弯曲的划分、弯曲形状的识别、层次结构；总结和归纳了线状要素的单一特征参数、组合特征参数以及各参数的几何意义。
(5)在探讨了线状要素形状二维性——弯曲性与方向性的基础上,运用BP神经网络系统将线状要素按其形状进行分类与分段,拟对不同形状的线状要素和线状要素子段采用不同的化简模型和参数。
(6)阐述了线状要素化简可能带来的三个损失——点位精度、拓扑一致性、形状相似性,并简要分析了这三者之间的关系。在线状要素形状相似性分析的基础上,分析了不同的线状要素化简模型在化简中对形状的影响,得出了Douglas-Peucker化简模型具有精度损失最小、形状保真度最高的结论。
As an important characteristic of spatial cognition and a cognition result of graphic structure, pattern and distributing condition, shape plays a significant role in map generalization. Structural recognition of geographical features is essential in map generalization, which includes the analysis in distributing pattern and shape characteristic. Therefore, map generalization overall strategy could be established on the basis of the acquired distributing rule of geographical features and phenomena.Secondly, whereas a feature should be kept shape similarity in multi-scale representation, shape fidelity takes priority in generalization algorithm. Thirdly, shape similarity is an important index in map generalization evaluation. As an aspect in the field of cognition, shape recognition carries subjectivity and uncertainty. Therefore, shape analysis and recognition in map generalization is challanging and practical as well. This dissertation focused on the following:
(1) Theoretical bases supporting shape recognition are systematically summarized. From the start of the definition of shape, the dissertation introduces three models about pattern recognition——template matching model, prototype matching model and feature matching model in a systematical way and expatiates on human's cognitive regularity to shape. From the angle of the science of computer and information, the method or model about shape recognition and characteristics of shape representation of features in cartography are introduced and summarized.
(2) The shape characteristic value of area feature in GIS and the model of calculating shape similarity distance are interpreted in detail. The Fourier shape descriptor and shape number to calculating similarity distance of shape are placed great emphasis.The convergence speed and descriptive accuracy are analyzed when the Fourier descriptor applied in describing different kinds of shape. The method to obtain shape number with three invariances which is proper to building is devised and that the shape number with different scale exists influence on shape description is researched.
(3) Under the elicitation of prototype matching model of pattern recognition in cognition psychology, the dissertation presents the method of simplification of building based on dynamic template matching. The theory and operational processing of the method are provided from the aspects of prototype template designing, dynamic template creating, template setting and detecting validity of simplification result. The method has been proved practical by data experiment.
(4) shape characteristic unit——bend of line feature and its shape characteristic parameters are analysed. The partition, hierarchy of bend of line feature are explained. Simple shape characteristic parameters and composite shape characteristic parameters and their geometrical meaning are summarized.
(5) On the basis of the research of two dimension attributes of shape of line feature, the line feature is devided into different classes and is partitioned into many segments which have same shape characteristics, and the segments are simplified through different simplification algorithms and simplification threshold.
(6) The dissertation expatiates on the possible losses as a result of the simplification of line feature——position accuracy, topology consistency and shape similarity. The relations among the above-mentioned losses are also presented. The shape deformation of different line simplification model is analysed and the conclusion is drawed that Douglas-peucker simplification model is the most proper in position accuracy and fidelity of shape.
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