Research on 3D scan debris reconstruction by using artificial fish algorithm

doi:10.13474/j.cnki.11-2246.2019.0095

Abstract

Abstract: Previous approaches for reconstructing fragments rely mainly on a single characteristic and thus may cause accumulative errors.In this paper,we present a global optimal matching method for 3D fragments by using artificial fish school algorithm.The proposed method first extracts multi-featured elements from the point cloud of the fragments.Combined with texture and expert knowledge,rough set theory is then applied to classify multiple types of fragments.The artificial fish school algorithm is subsequently adopted to achieve optimal matching results.Results indicate that the proposed method is powerful,robust,and independent of initial position.The proposed method can be a new efficient tool for the global matching of fragments.

Key words: 3D laser scanning, feature extraction, rough set, artificial fish school algorithm, global matching

CLC Number:

P208

LIU Ensheng, CHENG Xiaojun, HUANG Yuhua. Research on 3D scan debris reconstruction by using artificial fish algorithm[J]. 测绘通报, 2019, 0(3): 137-140.

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