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Multi-Constrained Optimization Method of Line Segment Extraction Based on Multi-Scale Image Space

1
Beijing Key Lab of Spatial Information Integration & Its Applications, School of Earth and Space Sciences, Peking University, Beijing 100871, China
2
School of Geographic and Environmental Science, Tianjin Normal University, Tianjin 300387, China
3
Leicester Institute for Space and Earth Observation, Centre for Landscape & Climate Research, School of Geography, Geology and the Environment, University of Leicester, Leicester, LE1 7RH, UK
4
Information Engineering College, Capital Normal University, Beijing 100048, China
5
Guangxi Colleges and Universities Key Laboratory of Unmanned Aerial Vehicle (UAV) Remote Sensing, Guilin University of Aerospace Technology, Guilin 541004, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
ISPRS Int. J. Geo-Inf. 2019, 8(4), 183; https://doi.org/10.3390/ijgi8040183
Received: 5 March 2019 / Revised: 31 March 2019 / Accepted: 4 April 2019 / Published: 8 April 2019
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Abstract

Image-based line segment extraction plays an important role in a wide range of applications. Traditional line segment extraction algorithms focus on the accuracy and efficiency, without considering the integrity. Serious line segmentation fracture problems caused by image quality will result in poor subsequent applications. To solve this problem, a multi-constrained line segment extraction method, based on multi-scale image space, is presented. Firstly, using Gaussian down-sampling with a classical line segment detection method, a multi-scale image space is constructed to extract line segments in each image scale and all line segments are projected onto the original image. Then, a new line segment optimization and purification strategy is proposed with the horizontal and vertical distances and angle geometric constraint relationships between line segments to merge fracture line segments and delete redundant line segments. Finally, line segments with adjacent positions are optimized using the grayscale constraint relationship, based on normalized cross-correlation similarity criterion for realizing the second optimization of fracture line segments. Compared with mainstream line segment detector and edge drawing lines methods, experimental results (i.e., indoor, outdoor, and aerial images) indicate the validity and superiority of our proposed methods which can extract longer and more complete line segments. View Full-Text
Keywords: line segment extraction; multi-scale image space; optimization; purification; geometric constraint; grayscale constraint line segment extraction; multi-scale image space; optimization; purification; geometric constraint; grayscale constraint
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Sun, Y.; Wang, Q.; Tansey, K.; Ullah, S.; Liu, F.; Zhao, H.; Yan, L. Multi-Constrained Optimization Method of Line Segment Extraction Based on Multi-Scale Image Space. ISPRS Int. J. Geo-Inf. 2019, 8, 183.

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