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运用人工鱼群算法的3D扫描碎片重建探究
引用本文:刘恩盛,程效军,黄玉花.运用人工鱼群算法的3D扫描碎片重建探究[J].测绘通报,2019,0(3):137-140.
作者姓名:刘恩盛  程效军  黄玉花
作者单位:同济大学测绘与地理信息学院,上海200092;井冈山大学,江西 吉安343009;同济大学测绘与地理信息学院,上海200092;现代工程测量国家测绘地理信息局重点实验室,上海200092;井冈山大学,江西 吉安,343009
基金项目:广州市科技计划(201704030102)
摘    要:针对传统三维碎片拼接匹配过程中依赖单一特征及存在误差累积的问题,提出了一种运用鱼群算法的全局最优匹配方法。该方法先对碎片点云数据进行多特征提取,结合纹理、专家经验信息对混合在一起的多种类型碎片进行粗糙集分类,之后采用鱼群算法的最优解求得最佳匹配方案。实例验证所提全局匹配方法具有能力强、与初始位置无关及较强的稳健性等特点,为三维碎片的全局匹配提供了一种有效的解决方案。

关 键 词:三维激光扫描  特征提取  粗糙集  鱼群算法  全局匹配
收稿时间:2018-04-02
修稿时间:2018-12-17

Research on 3D scan debris reconstruction by using artificial fish algorithm
LIU Ensheng,CHENG Xiaojun,HUANG Yuhua.Research on 3D scan debris reconstruction by using artificial fish algorithm[J].Bulletin of Surveying and Mapping,2019,0(3):137-140.
Authors:LIU Ensheng  CHENG Xiaojun  HUANG Yuhua
Institution:1. College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China;2. Jinggangshan University, Ji'an 343009, China;3. Key Laboratory of Advancecd Engineering Surveying of NASMG, Shanghai 200092, China
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.
Keywords:3D laser scanning  feature extraction  rough set  artificial fish school algorithm  global matching  
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