Line Segment Matching Fusing Local Gradient Order and Non-Local Structure Information Article Swipe
YOU?
·
· 2021
· Open Access
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· DOI: https://doi.org/10.3390/app12010127
Line segment matching is essential for industrial applications such as scene reconstruction, pattern recognition, and VSLAM. To achieve good performance under the scene with illumination changes, we propose a line segment matching method fusing local gradient order and non-local structure information. This method begins with intensity histogram multiple averaging being utilized for adaptive partitioning. After that, the line support region is divided into several sub-regions, and the whole image is divided into a few intervals. Then the sub-regions are encoded by local gradient order, and the intervals are encoded by non-local structure information of the relationship between the sampled points and the anchor points. Finally, two histograms of the encoded vectors are, respectively, normalized and cascaded. The proposed method was tested on the public datasets and compared with previous methods, which are the line-junction-line (LJL), the mean-standard deviation line descriptor (MSLD) and the line-point invariant (LPI). Experiments show that our approach has better performance than the representative methods in various scenes. Therefore, a tentative conclusion can be drawn that this method is robust and suitable for various illumination changes scenes.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app12010127
- https://www.mdpi.com/2076-3417/12/1/127/pdf?version=1640349499
- OA Status
- gold
- Cited By
- 2
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4200052462
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4200052462Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/app12010127Digital Object Identifier
- Title
-
Line Segment Matching Fusing Local Gradient Order and Non-Local Structure InformationWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-12-23Full publication date if available
- Authors
-
Weibo Cai, Jintao Cheng, Juncan Deng, Yubin Zhou, Hua Xiao, Jian Zhang, Kaiqing LuoList of authors in order
- Landing page
-
https://doi.org/10.3390/app12010127Publisher landing page
- PDF URL
-
https://www.mdpi.com/2076-3417/12/1/127/pdf?version=1640349499Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2076-3417/12/1/127/pdf?version=1640349499Direct OA link when available
- Concepts
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Histogram, Artificial intelligence, Computer vision, Line (geometry), Pattern recognition (psychology), Matching (statistics), Computer science, Line segment, Point (geometry), Invariant (physics), Mathematics, Image (mathematics), Mathematical physics, Geometry, StatisticsTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2024: 1, 2022: 1Per-year citation counts (last 5 years)
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35Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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