Assessing the efficiency of shape-based functions and descriptors in multi-scale matching of linear objects

被引:12
作者
Abbaspour, Rahim Ali [1 ]
Chehreghan, Alireza [1 ]
Karimi, Amer [1 ]
机构
[1] Univ Tehran, Sch Surveying & Geospatial Engn, Coll Engn, Tehran, Iran
关键词
Functions and descriptors of shape; linear objects matching; similarity; multi-scale datasets; QUALITY ASSESSMENT; ROAD NETWORKS; CONFLATION; VGI; OPTIMIZATION; INTEGRATION; AUTHORITY; DATABASES;
D O I
10.1080/10106049.2017.1316777
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The study of objects similarity in terms of shape has various applications such as determining the similarity degree in object matching. To this end, different functions and descriptors have been used. However, efficiency of each method used in various studies for solving linear object matching in datasets with either different or similar scales or sources has not been studied yet. This article studies the efficiency of the most important functions (i.e. turning, signature, and tangent) along with shape descriptors (i.e. shape context, LORD, and shape signature) in vector datasets with different scales and sources. For this purpose, three datasets of roads network with different sources and scales were employed. Results showed the greater efficiency of the turning function compared to the other methods. In addition to being able to identify corresponding objects in multi-scale datasets, it can improve matching and is capable of discovering shape difference in non-corresponding objects.
引用
收藏
页码:879 / 892
页数:14
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