Abstract

Shape index is introduced to explore the target recognition problem from laser radar (Ladar) range imagery. A raw Ladar scene range image is transformed into a height-range image and a horizontal-range image. Then they are compared with a model library in which every model target includes six selected samples based on the principles of raising recognition rate and shortening computation time. We experimentally demonstrate that the proposed recognition approach can resolve the out-of-plane and rotation-invariant target recognition problem with a high recognition rate.

© 2010 OSA

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  1. J. G. Verly, R. L. Delanoy, and D. E. Dudgeon, “Model-based system for automatic target recognition from forward-looking laser-radar imagery,” Opt. Eng. 31(12), 2540–2552 (1992).
    [CrossRef]
  2. K. Mori, T. Takahashi, and I. Ide, “Fog density recognition by in-vehicle camera and millimeter wave radar,” Int. J. Control 3(5), 1173–1182 (2007).
  3. N. R. Pal, T. C. Cahoon, J. C. Bezdek, and K. Pal, “A new approach to target recognition for Ladar data,” IEEE Trans. Fuzzy Syst. 9(1), 44–52 (2001).
    [CrossRef]
  4. J. Sun, O. Li, W. Lu, and Q. Wang, “Image recognition of laser radar using linear SVM correlation filter,” Chin. Opt. Lett. 5(9), 549–551 (2007).
  5. N. A. Watts, “Calculating the principal views of a polyhedron,” In Proceedings of the 9th International Conference on Pattern Recognition, 316–322 (1988).
  6. D. Eggert and K. Bowyer, “Computing the perspective projection aspect graph of solids of revolution,” IEEE Trans. Pattern Anal. Mach. Intell. 15(2), 109–128 (1993).
    [CrossRef]
  7. V. Shantaram, and M. Hanmandlu, “Contour-based matching technique for 3D object recognition,” in Proceedings of the International Conference on Information Technology, 274–279 (2002).
  8. Y. S. and A. Farag, “3D objects coding and recognition using surface signatures,” in Proceedings of the 15th International Conference on Pattern Recognition 4, 571–574 (2000).
  9. A. Johnson, Ph. D. thesis, “A Representation for 3-D Surface Matching,” (Robotics Institute, Carnegie Mellon University, Pittsburgh, 1997).
  10. S.-H. Hong and B. Javidi, “Distortion-tolerant 3D recognition of occluded objects using computational integral imaging,” Opt. Express 14(25), 12085–12095 (2006).
    [CrossRef] [PubMed]
  11. S. Correa, and L. Shapiro, “A new signature-based method for efficient 3-D object recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition 1, 769–776 (2001).
  12. Q. Wang, Q. Li, Z. Chen, J. Sun, and R. Rao, “Range image noise suppression in laser imaging system,” Opt. Laser Technol. 41(2), 140–147 (2009).
    [CrossRef]
  13. D. Chitra, and K. J. Anil, “Shape spectra based view grouping for free-form objects,” in the 1995 International Conference on Image Processing 3, 340–343 (1995).
  14. P. J. Flynn, and A. K. Jain, “On reliable curvature estimation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 110–116 (1989).
  15. H. Chen and B. Bhanu, “3D free-form object recognition in range images using local surface patches,” Pattern Recognit. Lett. 28(10), 1252–1262 (2007).
    [CrossRef]
  16. P. J. Besl and R. C. Jain, “Segmentation through variable-order surface fitting,” IEEE Trans. Pattern Anal. Mach. Intell. 10(2), 167–192 (1988).
    [CrossRef]
  17. Z. Y. Zhang, “Iterative point matching for registration of free-form curves and surfaces,” Int. J. Comput. Vis. 13(2), 119–152 (1994).
    [CrossRef]
  18. A. N. Vasile and R. M. Marino, “Pose-independent automatic target detection and recognition using 3D laser radar imagery,” Lincoln Lab. J. 15(1), 61–78 (2005).
  19. W. Li, S. Jianfeng, and W. Qi, “Model-based algorithm for rotation-invariant target recognition using laser radar range imager,” J. Russ. Laser Res. 30(6), 615–625 (2009).
    [CrossRef]

2009

Q. Wang, Q. Li, Z. Chen, J. Sun, and R. Rao, “Range image noise suppression in laser imaging system,” Opt. Laser Technol. 41(2), 140–147 (2009).
[CrossRef]

W. Li, S. Jianfeng, and W. Qi, “Model-based algorithm for rotation-invariant target recognition using laser radar range imager,” J. Russ. Laser Res. 30(6), 615–625 (2009).
[CrossRef]

2007

H. Chen and B. Bhanu, “3D free-form object recognition in range images using local surface patches,” Pattern Recognit. Lett. 28(10), 1252–1262 (2007).
[CrossRef]

K. Mori, T. Takahashi, and I. Ide, “Fog density recognition by in-vehicle camera and millimeter wave radar,” Int. J. Control 3(5), 1173–1182 (2007).

J. Sun, O. Li, W. Lu, and Q. Wang, “Image recognition of laser radar using linear SVM correlation filter,” Chin. Opt. Lett. 5(9), 549–551 (2007).

2006

2005

A. N. Vasile and R. M. Marino, “Pose-independent automatic target detection and recognition using 3D laser radar imagery,” Lincoln Lab. J. 15(1), 61–78 (2005).

2001

N. R. Pal, T. C. Cahoon, J. C. Bezdek, and K. Pal, “A new approach to target recognition for Ladar data,” IEEE Trans. Fuzzy Syst. 9(1), 44–52 (2001).
[CrossRef]

1994

Z. Y. Zhang, “Iterative point matching for registration of free-form curves and surfaces,” Int. J. Comput. Vis. 13(2), 119–152 (1994).
[CrossRef]

1993

D. Eggert and K. Bowyer, “Computing the perspective projection aspect graph of solids of revolution,” IEEE Trans. Pattern Anal. Mach. Intell. 15(2), 109–128 (1993).
[CrossRef]

1992

J. G. Verly, R. L. Delanoy, and D. E. Dudgeon, “Model-based system for automatic target recognition from forward-looking laser-radar imagery,” Opt. Eng. 31(12), 2540–2552 (1992).
[CrossRef]

1988

P. J. Besl and R. C. Jain, “Segmentation through variable-order surface fitting,” IEEE Trans. Pattern Anal. Mach. Intell. 10(2), 167–192 (1988).
[CrossRef]

Besl, P. J.

P. J. Besl and R. C. Jain, “Segmentation through variable-order surface fitting,” IEEE Trans. Pattern Anal. Mach. Intell. 10(2), 167–192 (1988).
[CrossRef]

Bezdek, J. C.

N. R. Pal, T. C. Cahoon, J. C. Bezdek, and K. Pal, “A new approach to target recognition for Ladar data,” IEEE Trans. Fuzzy Syst. 9(1), 44–52 (2001).
[CrossRef]

Bhanu, B.

H. Chen and B. Bhanu, “3D free-form object recognition in range images using local surface patches,” Pattern Recognit. Lett. 28(10), 1252–1262 (2007).
[CrossRef]

Bowyer, K.

D. Eggert and K. Bowyer, “Computing the perspective projection aspect graph of solids of revolution,” IEEE Trans. Pattern Anal. Mach. Intell. 15(2), 109–128 (1993).
[CrossRef]

Cahoon, T. C.

N. R. Pal, T. C. Cahoon, J. C. Bezdek, and K. Pal, “A new approach to target recognition for Ladar data,” IEEE Trans. Fuzzy Syst. 9(1), 44–52 (2001).
[CrossRef]

Chen, H.

H. Chen and B. Bhanu, “3D free-form object recognition in range images using local surface patches,” Pattern Recognit. Lett. 28(10), 1252–1262 (2007).
[CrossRef]

Chen, Z.

Q. Wang, Q. Li, Z. Chen, J. Sun, and R. Rao, “Range image noise suppression in laser imaging system,” Opt. Laser Technol. 41(2), 140–147 (2009).
[CrossRef]

Delanoy, R. L.

J. G. Verly, R. L. Delanoy, and D. E. Dudgeon, “Model-based system for automatic target recognition from forward-looking laser-radar imagery,” Opt. Eng. 31(12), 2540–2552 (1992).
[CrossRef]

Dudgeon, D. E.

J. G. Verly, R. L. Delanoy, and D. E. Dudgeon, “Model-based system for automatic target recognition from forward-looking laser-radar imagery,” Opt. Eng. 31(12), 2540–2552 (1992).
[CrossRef]

Eggert, D.

D. Eggert and K. Bowyer, “Computing the perspective projection aspect graph of solids of revolution,” IEEE Trans. Pattern Anal. Mach. Intell. 15(2), 109–128 (1993).
[CrossRef]

Hong, S.-H.

Ide, I.

K. Mori, T. Takahashi, and I. Ide, “Fog density recognition by in-vehicle camera and millimeter wave radar,” Int. J. Control 3(5), 1173–1182 (2007).

Jain, R. C.

P. J. Besl and R. C. Jain, “Segmentation through variable-order surface fitting,” IEEE Trans. Pattern Anal. Mach. Intell. 10(2), 167–192 (1988).
[CrossRef]

Javidi, B.

Jianfeng, S.

W. Li, S. Jianfeng, and W. Qi, “Model-based algorithm for rotation-invariant target recognition using laser radar range imager,” J. Russ. Laser Res. 30(6), 615–625 (2009).
[CrossRef]

Li, O.

Li, Q.

Q. Wang, Q. Li, Z. Chen, J. Sun, and R. Rao, “Range image noise suppression in laser imaging system,” Opt. Laser Technol. 41(2), 140–147 (2009).
[CrossRef]

Li, W.

W. Li, S. Jianfeng, and W. Qi, “Model-based algorithm for rotation-invariant target recognition using laser radar range imager,” J. Russ. Laser Res. 30(6), 615–625 (2009).
[CrossRef]

Lu, W.

Marino, R. M.

A. N. Vasile and R. M. Marino, “Pose-independent automatic target detection and recognition using 3D laser radar imagery,” Lincoln Lab. J. 15(1), 61–78 (2005).

Mori, K.

K. Mori, T. Takahashi, and I. Ide, “Fog density recognition by in-vehicle camera and millimeter wave radar,” Int. J. Control 3(5), 1173–1182 (2007).

Pal, K.

N. R. Pal, T. C. Cahoon, J. C. Bezdek, and K. Pal, “A new approach to target recognition for Ladar data,” IEEE Trans. Fuzzy Syst. 9(1), 44–52 (2001).
[CrossRef]

Pal, N. R.

N. R. Pal, T. C. Cahoon, J. C. Bezdek, and K. Pal, “A new approach to target recognition for Ladar data,” IEEE Trans. Fuzzy Syst. 9(1), 44–52 (2001).
[CrossRef]

Qi, W.

W. Li, S. Jianfeng, and W. Qi, “Model-based algorithm for rotation-invariant target recognition using laser radar range imager,” J. Russ. Laser Res. 30(6), 615–625 (2009).
[CrossRef]

Rao, R.

Q. Wang, Q. Li, Z. Chen, J. Sun, and R. Rao, “Range image noise suppression in laser imaging system,” Opt. Laser Technol. 41(2), 140–147 (2009).
[CrossRef]

Sun, J.

Q. Wang, Q. Li, Z. Chen, J. Sun, and R. Rao, “Range image noise suppression in laser imaging system,” Opt. Laser Technol. 41(2), 140–147 (2009).
[CrossRef]

J. Sun, O. Li, W. Lu, and Q. Wang, “Image recognition of laser radar using linear SVM correlation filter,” Chin. Opt. Lett. 5(9), 549–551 (2007).

Takahashi, T.

K. Mori, T. Takahashi, and I. Ide, “Fog density recognition by in-vehicle camera and millimeter wave radar,” Int. J. Control 3(5), 1173–1182 (2007).

Vasile, A. N.

A. N. Vasile and R. M. Marino, “Pose-independent automatic target detection and recognition using 3D laser radar imagery,” Lincoln Lab. J. 15(1), 61–78 (2005).

Verly, J. G.

J. G. Verly, R. L. Delanoy, and D. E. Dudgeon, “Model-based system for automatic target recognition from forward-looking laser-radar imagery,” Opt. Eng. 31(12), 2540–2552 (1992).
[CrossRef]

Wang, Q.

Q. Wang, Q. Li, Z. Chen, J. Sun, and R. Rao, “Range image noise suppression in laser imaging system,” Opt. Laser Technol. 41(2), 140–147 (2009).
[CrossRef]

J. Sun, O. Li, W. Lu, and Q. Wang, “Image recognition of laser radar using linear SVM correlation filter,” Chin. Opt. Lett. 5(9), 549–551 (2007).

Zhang, Z. Y.

Z. Y. Zhang, “Iterative point matching for registration of free-form curves and surfaces,” Int. J. Comput. Vis. 13(2), 119–152 (1994).
[CrossRef]

Chin. Opt. Lett.

IEEE Trans. Fuzzy Syst.

N. R. Pal, T. C. Cahoon, J. C. Bezdek, and K. Pal, “A new approach to target recognition for Ladar data,” IEEE Trans. Fuzzy Syst. 9(1), 44–52 (2001).
[CrossRef]

IEEE Trans. Pattern Anal. Mach. Intell.

D. Eggert and K. Bowyer, “Computing the perspective projection aspect graph of solids of revolution,” IEEE Trans. Pattern Anal. Mach. Intell. 15(2), 109–128 (1993).
[CrossRef]

P. J. Besl and R. C. Jain, “Segmentation through variable-order surface fitting,” IEEE Trans. Pattern Anal. Mach. Intell. 10(2), 167–192 (1988).
[CrossRef]

Int. J. Comput. Vis.

Z. Y. Zhang, “Iterative point matching for registration of free-form curves and surfaces,” Int. J. Comput. Vis. 13(2), 119–152 (1994).
[CrossRef]

Int. J. Control

K. Mori, T. Takahashi, and I. Ide, “Fog density recognition by in-vehicle camera and millimeter wave radar,” Int. J. Control 3(5), 1173–1182 (2007).

J. Russ. Laser Res.

W. Li, S. Jianfeng, and W. Qi, “Model-based algorithm for rotation-invariant target recognition using laser radar range imager,” J. Russ. Laser Res. 30(6), 615–625 (2009).
[CrossRef]

Lincoln Lab. J.

A. N. Vasile and R. M. Marino, “Pose-independent automatic target detection and recognition using 3D laser radar imagery,” Lincoln Lab. J. 15(1), 61–78 (2005).

Opt. Eng.

J. G. Verly, R. L. Delanoy, and D. E. Dudgeon, “Model-based system for automatic target recognition from forward-looking laser-radar imagery,” Opt. Eng. 31(12), 2540–2552 (1992).
[CrossRef]

Opt. Express

Opt. Laser Technol.

Q. Wang, Q. Li, Z. Chen, J. Sun, and R. Rao, “Range image noise suppression in laser imaging system,” Opt. Laser Technol. 41(2), 140–147 (2009).
[CrossRef]

Pattern Recognit. Lett.

H. Chen and B. Bhanu, “3D free-form object recognition in range images using local surface patches,” Pattern Recognit. Lett. 28(10), 1252–1262 (2007).
[CrossRef]

Other

D. Chitra, and K. J. Anil, “Shape spectra based view grouping for free-form objects,” in the 1995 International Conference on Image Processing 3, 340–343 (1995).

P. J. Flynn, and A. K. Jain, “On reliable curvature estimation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 110–116 (1989).

N. A. Watts, “Calculating the principal views of a polyhedron,” In Proceedings of the 9th International Conference on Pattern Recognition, 316–322 (1988).

V. Shantaram, and M. Hanmandlu, “Contour-based matching technique for 3D object recognition,” in Proceedings of the International Conference on Information Technology, 274–279 (2002).

Y. S. and A. Farag, “3D objects coding and recognition using surface signatures,” in Proceedings of the 15th International Conference on Pattern Recognition 4, 571–574 (2000).

A. Johnson, Ph. D. thesis, “A Representation for 3-D Surface Matching,” (Robotics Institute, Carnegie Mellon University, Pittsburgh, 1997).

S. Correa, and L. Shapiro, “A new signature-based method for efficient 3-D object recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition 1, 769–776 (2001).

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Figures (15)

Fig. 1
Fig. 1

(a) Top view of an aircraft, (b) its range image, and (c) its shape index image.

Fig. 2
Fig. 2

Feature point locations in a range image.

Fig. 3
Fig. 3

Demonstration of a local surface patch.

Fig. 4
Fig. 4

Transformation from range value to height-range and horizontal-range values [19].

Fig. 5
Fig. 5

(a) and (e) 3D models of a car and a bus (b) and (f) Corresponding noise-free range images, (c) and (g) Corresponding height-range images, (d) and (h) Corresponding horizontal-range image.

Fig. 6
Fig. 6

3-D model library.

Fig. 7
Fig. 7

Simulated noise-free model target range images.

Fig. 8
Fig. 8

Average V ¯ GOF as a function of training-set size.

Fig. 9
Fig. 9

Recognition performance comparisons of one sample to five samples.

Fig. 10
Fig. 10

Simulated noise-free range images.

Fig. 11
Fig. 11

V ¯ GOF as a function of depression angles.

Fig. 12
Fig. 12

V ¯ GOF as a function of depression angles.

Fig. 13
Fig. 13

V ¯ GOF as a function of depression angles.

Fig. 14
Fig. 14

Noise measured targets with arbitrary depression angles and azimuth angles.

Fig. 15
Fig. 15

V ¯ GOF as a function of depression angles and azimuth angles.

Tables (1)

Tables Icon

Table 1 Surface Type Labels Based on Surface Curvature Sign

Equations (7)

Equations on this page are rendered with MathJax. Learn more.

S i ( p ) = 1 2 1 π tan 1 κ 1 ( p ) + κ 2 ( p ) κ 1 ( p ) κ 2 ( p ) ,
μ = 1 W j = 1 W S i ( j ) 0 α , β 1.
Q = { pixels Q , Q P ε } a n d a cos ( n p n h ) < B ,
χ 2 ( M , N ) = i ( m i n i ) 2 m i + n i ,
V GOF ( s , m ) = ε 2 N p t MSE .
V ¯ GOF ( s , m i ) = V GOF ( s , m i ) j = 1 R V GOF ( s , m j ) .
H = L sin A , T = L cos A .

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