Research on the 3D Sonar Single-frame Reconstruction Based on Local Outlier Factor Algorithm

doi:10.3969/j.issn.1000-1093.2020.03.016

Abstract

Abstract: 3D sonar always acquires the data point with outliers in the complex marine environment, which affects the post processing and visualization of point cloud. 3D beamforming imaging, maximum filtering and coordinate transformation are made for the sonar data to obtain the original point cloud. The local outlier factor (LOF) algorithm is used to eliminate the abnormal points, and a modified triangulation growing method is used for single-frame reconstruction. In the modified triangulation growing method, the crucial process of ‘the third point’ finding in triangular mesh generation is simplified. A denoising method based on LOF algorithm can be used to eliminate the points not belonging to the target under the premise in keeping the real contour of target compared with the traditional threshold denoising method. And the 3D reconstruction result of more realistic target contour can be achieved from the sonar data obtained by the proposed denoising method. Key

Key words: three-dimensionalsonar, pointcloud, localoutlierfactor, triangulationmesh, denoising, single-framereconstruction

CLC Number:

ZENG Teng, ZHANG Chunhua, WANG Peng. Research on the 3D Sonar Single-frame Reconstruction Based on Local Outlier Factor Algorithm[J]. Acta Armamentarii, 2020, 41(3): 552-558.

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第41卷第3期2020 年3月
兵工学报ACTA ARMAMENTARII
Vol.41No.3Mar.2020

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