A Multisource Contour Matching Method Considering the Similarity of Geometric Features

doi:10.11947/j.JGGS.2020.0308

Abstract

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 the 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

Wenyue GUO, Anzhu YU, Qun SUN, Shaomei LI, Qing XU, Bowei WEN, Yuanfu LI. A Multisource Contour Matching Method Considering the Similarity of Geometric Features[J]. Journal of Geodesy and Geoinformation Science, 2020, 3(3): 76-87.

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Original contour	Candidate contour	Similarity using the proposed method
Original contour	Candidate contour	Chord measure	Angle measure	CANV measure
A	B₁	0.4390	0.4634	0.6296
A	B₂	0.3659	0.2927	0.3704
Similarity differential		0.0731	0.1707	0.2592

	A	B₁	B₂
Node quantity	42	30	26
LCSS length	42	18	14
Curve length (m)	2700.88	1155.48	1319.34
Similarity with A	1.0000	0.4286	0.3333

	A	B₁	B₂
Node quantity	46	44	26
LCSS length	46	20	17
Curve length (m)	2978.13	2494.12	488.44
Similarity with A	1.0000	0.4348	0.3696

Original contour	Candidate contours	Fréchet distance /m	Average Fréchet distance /m	Similarity proposed
A	B₁	1108.85	522.31	0.5273
A	B₂	787.99	285.26	0.2000
Operation time/s		0.4270	0.8020	0.0820
Matching result		B₂	B₂	B₁

Contour data		Matching quantity	Correct matching quantity	Erroneous matching quantity	Unmatching quantity	Matching recall /(%)	Matching accuracy /(%)	Average operation time/s
Original contour quantity	Candidate contour quantity	Matching quantity	Correct matching quantity	Erroneous matching quantity	Unmatching quantity	Matching recall /(%)	Matching accuracy /(%)	Average operation time/s
1757	3792	1553	1415	138	204	87.40	91.11	0.11