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http://dx.doi.org/10.22640/lxsiri.2020.50.2.155

Comparison of Open Source based Algorithms and Filtering Methods for UAS Image Processing  

Kim, Tae Hee (Department of Urban Construction Engineering, Incheon National University)
Lee, Yong Chang (Department of Urban Construction Engineering, Incheon National University)
Publication Information
Journal of Cadastre & Land InformatiX / v.50, no.2, 2020 , pp. 155-168 More about this Journal
Abstract
Open source is a key growth engine of the 4th industrial revolution, and the continuous development and use of various algorithms for image processing is expected. The purpose of this study is to examine the effectiveness of the UAS image processing open source based algorithm by comparing and analyzing the water reproduction and moving object filtering function and the time required for data processing in 3D reproduction. Five matching algorithms were compared based on recall and processing speed through the 'ANN-Benchmarks' program, and HNSW (Hierarchical Navigable Small World) matching algorithm was judged to be the best. Based on this, 108 algorithms for image processing were constructed by combining each methods of triangulation, point cloud data densification, and surface generation. In addition, the 3D reproduction and data processing time of 108 algorithms for image processing were studied for UAS (Unmanned Aerial System) images of a park adjacent to the sea, and compared and analyzed with the commercial image processing software 'Pix4D Mapper'. As a result of the study, the algorithms that are good in terms of reproducing water and filtering functions of moving objects during 3D reproduction were specified, respectively, and the algorithm with the lowest required time was selected, and the effectiveness of the algorithm was verified by comparing it with the result of 'Pix4D Mapper'.
Keywords
Open source; Image processing; Algorithm; Filtering;
Citations & Related Records
Times Cited By KSCI : 8  (Citation Analysis)
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