Adaptive 3D Mesh Model Reconstruction Based on Industrial CT Images

Ling Li; Heng Jin; Jie Liu; Chao Long; Yunyong He; Zhongming Li; Liming Duan

doi:10.3788/AOS221477

Acta Optica Sinica, Volume. 43, Issue 3, 0334001(2023)

Adaptive 3D Mesh Model Reconstruction Based on Industrial CT Images

Ling Li^1,2, Heng Jin^1,2, Jie Liu^1,3, Chao Long^1,3, Yunyong He^1,3, Zhongming Li^1,2, and Liming Duan^1,2、*

¹ICT Research Center, Key Laboratory of Optoelectronic Technology & Systems, Ministry of Education, Chongqing University, Chongqing 400044, China

²College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China

³College of Optoelectronic Engineering, Chongqing University, Chongqing 400044, China

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Figures & Tables(11)

Fig. 1. Results of image denoising by different algorithms. (a) Original image; (b) mean filtering; (c) Gaussian filtering; (d) median filtering; (e) nonlocal mean filtering; (f) bilateral filtering

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Fig. 2. Schematic of a voxel

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Fig. 3. Flow chart for creating an octree

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Fig. 4. Location of feature point. (a) Feature point is outside the voxel; (b) feature point is inside the voxel

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Fig. 5. Connection mode of quadrilateral

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Fig. 6. Mode of dividing quadrilateral

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Fig. 7. Reconstruction results of different algorithms. (a) MC algorithm; (b) proposed algorithm

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Fig. 8. Using different simplification algorithms to simplify the gear model. (a) Mesh model; (b) algorithm of Ref. [9]; (c) algorithm of Ref. [12]; (d) proposed algorithm

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Fig. 9. Engine models under different simplified parameters. (a) Unsimplified model ( $φ = - 0.01$ ); (b) simplified model 1 ( $φ = 0.01$ ); (c) simplified model 2 ( $φ = 0.1$ ); (d) simplified model 3 ( $φ = 1$ ); (e) simplified model 4 ( $φ = 10$ ); (f) simplified model 5 ( $φ = 100$ )

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Table 1. Proportion of each type of node under different simplified parameters

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Table 1. Proportion of each type of node under different simplified parameters

Simplified parameter $φ$	Proportion of internal node / %	Proportion of leaf node / %	Proportion of pseudo leaf node /%
-0.01	24.81	75.19	0
0.01	24.15	71.49	4.36
0.1	24.14	71.33	4.53
1	23.20	65.80	11.00
10	20.58	0.24	79.18
100	20.41	0	79.59

Table 2. Performance of proposed algorithm with different parameters

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Table 2. Performance of proposed algorithm with different parameters

Model	Simplified parameter $φ$	Simplification rate /%	Mesh quality /%
Gear	-0.01	0	100.00
	0.01	42.90	99.77
	0.1	43.20	99.76
	1	60.36	99.57
	10	90.09	99.17
	100	96.74	99.05
Engine	-0.01	0	100.00
	0.01	15.59	99.95
	0.1	16.58	99.94
	1	31.71	99.90
	10	79.68	99.60
	100	92.03	99.56

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Ling Li, Heng Jin, Jie Liu, Chao Long, Yunyong He, Zhongming Li, Liming Duan. Adaptive 3D Mesh Model Reconstruction Based on Industrial CT Images[J]. Acta Optica Sinica, 2023, 43(3): 0334001

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Paper Information

Category: X-Ray Optics

Received: Jul. 14, 2022

Accepted: Aug. 29, 2022

Published Online: Feb. 13, 2023

The Author Email: Duan Liming (duanliming163@163.com)

DOI:10.3788/AOS221477

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology