Point Cloud Foot Model Extraction Algorithm for 3D Foot Model Scanner

Author(s):  
Mucong Gao ◽  
Chunfang Li ◽  
Rui Yang ◽  
Minyong Shi ◽  
Jintian Yang
2018 ◽  
Vol 55 (11) ◽  
pp. 111003
Author(s):  
韩玉川 Han Yuchuan ◽  
侯贺 Hou He ◽  
白云瑞 Bai Yunrui ◽  
朱险峰 Zhu Xianfeng

Author(s):  
Feng Zhao ◽  
Gaurav Dhiman

Background: The two main stages are utilized for feature extraction, from which the first stage consists of a penalty weight to the neighbor graph’s edges. The edge penalty weights are minimized by the neighbor sub-graph extraction to produce the set of feature patterns. For noisy data, the second stage is helpful. Methodology: In order to realize the measurement of the geometric dimensions of the ship block, this paper uses the theory of computer vision and reverse engineering to obtain the data of the segmented-hull with the method of digitizing the physical parts based on the vision, and processes the data by using the relevant knowledge of reverse engineering. Result: The results show that the efficiency of the edge extraction algorithm based on mathematical morphology is 30% higher than that of the mesh generation method. An adaptive corner detection algorithm based on the edge can adaptively determine the size of the support area and accurately detect the corner position. Conclusion: According to the characteristics of the point cloud of ship hull segment data, an adaptive corner detection algorithm based on the edge is adopted to verify its feasibility.


2018 ◽  
Vol 55 (2) ◽  
pp. 022801
Author(s):  
惠振阳 Hui Zhenyang ◽  
胡友健 Hu Youjian ◽  
康妍斐 Kang Yanfei

2019 ◽  
Vol 27 (5) ◽  
pp. 1218-1228
Author(s):  
陈华伟 CHEN Hua-wei ◽  
袁小翠 YUAN Xiao-cui ◽  
吴禄慎 WU Lu-chen ◽  
王晓辉 WANG Xiao-hui

2013 ◽  
Vol 475-476 ◽  
pp. 355-360
Author(s):  
Gui Zhen He

To achieve the trees three dimensional simulation, the most critical step is to extract the trees skeleton. This paper focuses on the point cloud contraction-based skeletal extraction algorithm, uses neighbors to build a transformation matrix, extract a discrete point set approximated to the real skeleton by Laplacian contraction, and constructs a 1D curve skeleton with the help of a weighted undirected graph and edge collapse algorithm. 1D curve form is more easy to operate, guide the reconstruction of three-dimensional model, solve the problem of incomplete data in the process of modeling .


2021 ◽  
Author(s):  
Jimin Ge ◽  
Zhaohui Deng ◽  
Zhongyang Li ◽  
Wei Li ◽  
Tao Liu ◽  
...  

Abstract Uneven surface quality often occurs when butt welds are manually grinding, so robotic weld grinding automation has become a fast-developing trend. Weld seam extraction and trajectory planning are important for automatic control of grinding process. However, most of the research on weld extraction is focused on before welding. Due to the irregular shape of the weld after welding, and too little work has been devoted to the weld identification after welding. Consequently, in this paper, a novel simple and efficient weld extraction algorithm is proposed, and the robot grinding path is planned. Firstly, a new flexible bracket structure for welding seam extraction is designed. Secondly, the weld seam section profile model is established, and the processing of spatial point cloud problem is transformed into the processing of two-dimensional point cloud problem. The least square method (LSM) based on threshold comparison is used to segment the weld seam, which greatly improved the processing speed and accuracy. Then the grinding path and pose are obtained according to the extracted weld space structure. Finally, a robotic welding seam automatic grinding system is built. Experiments show that the proposed method could well extract the irregular weld contour after welding and the grinding system built is reliable, which greatly improves the grinding efficiency.


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