Fig. 1. Schematic of linear intercept

Fig. 2. Linear intercepts between two points for different cases. (a) dp01 for feature point of p0; (b) dp10for non-feature point of p1; (c) d'p01 for feature point of p0; (d) dp12, dp21 for non-feature points of p1 and p2

Fig. 3. Phenomenon of misjudgment

Fig. 4. Feature points of Fandisk model. (a) Original model; (b) model reduced by 60%; (c) model with 20 dB noise

Fig. 5. Feature points of Bunny model. (a) Original model; (b) model with 10 dB noise; (c) model reduced by 60%

Fig. 6. Package diagram of model prototype. (a) Cross cuboid model; (b) workpiece model

Fig. 7. Feature points of cross cuboid model extracted under different δ values. (a) δ=10; (b) δ=9; (c) δ=8; (d) δ=7; (e) δ=6; (f) δ=5; (g) δ=4; (h) δ=3; (i) δ=2; (j) δ=1

Fig. 8. Feature points of workpiece model extracted under different δ values. (a) δ=10; (b) δ=9; (c) δ=8; (d) δ=7; (e) δ=6; (f) δ=5; (g) δ=4; (h) δ=3; (i) δ=2; (j) δ=1

Fig. 9. Extraction results of MSSV method under different intensities of noise. (a) 0 dB; (b) 5 dB; (c) 10 dB; (d) 15 dB

Fig. 10. Extraction results of NASD method under different intensities of noise. (a) 0 dB; (b) 5 dB; (c) 10 dB; (d) 15 dB

Fig. 11. Extraction results of proposed method under different intensities of noise. (a) 0 dB; (b) 5 dB; (c) 10 dB; (d) 15 dB

Fig. 12. Number of extracted feature points under different intensities of noise

Fig. 13. Extraction results of MSSV method. (a) Original model; (b) model reduced by 10%; (c) model reduced by 30%; (d)model reduced by 50%; (e) model reduced by 70%

Fig. 14. Extraction results of NASD method. (a) Original model ; (b) model reduced by 10%; (c) model reduced by 30%; (d) model reduced by 50%; (e) model reduced by 70%

Fig. 15. Extraction results of proposed method. (a) Original model; (b) model reduced by 10%; (c) model reduced by 30%; (d) model reduced by 50%; (e) model reduced by 70%