测绘学报 ›› 2019, Vol. 48 ›› Issue (5): 643-653.doi: 10.11947/j.AGCS.2019.20170688

• 地图学与地理信息 • 上一篇    下一篇

顾及几何特征相似性的多源等高线匹配方法

郭文月, 刘海砚, 孙群, 余岸竹, 丁梓越   

  1. 信息工程大学, 河南 郑州 450052
  • 收稿日期:2017-12-04 修回日期:2018-09-06 出版日期:2019-05-20 发布日期:2019-06-05
  • 作者简介:郭文月(1990-),女,博士生,研究方向为数字地图制图与遥感影像辅助更新。E-mail:guowyer@163.com
  • 基金资助:
    国家自然科学基金(41501446;41801388;41801313)

A multisource contour matching method considering the similarity of geometric features

GUO Wenyue, LIU Haiyan, SUN Qun, YU Anzhu, DING Ziyue   

  1. Information Engineering University, Zhengzhou 450052, China
  • Received:2017-12-04 Revised:2018-09-06 Online:2019-05-20 Published:2019-06-05
  • Supported by:
    The National Natural Science Foundation of China (Nos. 41501446;41801388;41801313)

摘要: 已有的多源等高线匹配方法主要基于等高线拓扑关系构建以及基于空间欧氏距离的相似性度量,缺少对等高线几何形态相似性的考虑,在等高线密集区域、图幅边界区域以及地形变化剧烈区域易产生误匹配情况。为此,本文提出一种基于几何特征相似性的由粗匹配到精匹配的多源等高线匹配策略。提出顾及局部特性的基于节点曲率以及法向量与横坐标轴夹角的混合特征描述测度,将等高线点序列转化为几何形态特征描述序列,引入最长公共子序列算法,量化计算多源等高线数据之间的相似程度,并依据相似度实现同名等高线匹配。利用模拟数据和真实数据对本文方法的可靠性和运行效率进行验证,试验证明,本文提出的匹配策略顾及了等高线空间位置特征和几何形态特征,能够保证较高的匹配精度和运行效率,并具有较好的适用范围。

关键词: 多源等高线匹配, 几何特征, 相似性度量, 最长公共子序列, 特征描述测度

Abstract: The existing multi-source contour matching studies have focused on the matching methods with consideration of topological relations and similarity measurement based on spatial Euclidean distance, while it is lack of taking the contour geometric features into account, which may lead to mismatching in map boundaries and areas with intensive contours or extreme terrain changes. In light of this, it is put forward that a matching strategy from coarse to precious based on the contour geometric features. The proposed matching strategy can be described as follows. Firstly, the point sequence is converted to feature sequence according to a feature descriptive function based on curvature and angle of normal vector.Then the level of similarity among multi-source contours is calculated by using the longest common subsequence solution. Accordingly, the identical contours could be matched based on above calculated results. In the experiment for the proposed method, the reliability and efficiency of the matching method are verified using simulative datasets and real datasets respectively. It has been proved that the proposed contour matching strategy has a high matching precision and good applicability.

Key words: multisource contour matching, geometric feature, similarity measurement, longest common subsequence, feature descriptor

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