G. E. Smith and B. G. Mobasseri, “Robust through-the-wall radar image classification using a target-model alignment procedure,” IEEE Trans. Image Process. 21, 754–767 (2012).

[CrossRef]

B. J. Chen, H. Z. Shu, H. Zhang, G. Chen, C. Toumoulin, J. L. Dillenseger, and L. M. Luo, “Quaternion Zernike moments and their invariants for color image analysis and object recognition,” Signal Process. 92, 308–318 (2012).

[CrossRef]

Z. J. Liu, Q. Li, Z. W. Xia, and Q. Wang, “Target recognition for small samples of ladar range image using classifier ensembles,” Opt. Eng. 51, 087201 (2012).

[CrossRef]

A. Antonio, M. Pilar, and S. Santiago, “3D scene retrieval and recognition with depth gradient images,” Pattern Recogn. Lett. 32, 1337–1353 (2011).

[CrossRef]

Q. Wang, L. Wang, and J. F. Sun, “Rotation-invariant target recognition in LADAR range imagery using model matching approach,” Opt. Express 18, 15349–15360 (2010).

[CrossRef]

Z. Chen and S. K. Sun, “A Zernike moment phase-based descriptor for local image representation and matching,” IEEE Trans. Image Process. 19, 205–219 (2010).

[CrossRef]

H. Abdi and L. J. Williams, “Principal component analysis,” WIREs Comp. Stat. 2, 433–459 (2010).

[CrossRef]

C. Singh and E. Walia, “Fast and numerically stable methods for the computation of Zernike moments,” Pattern Recogn. 43, 2497–2506 (2010).

[CrossRef]

Z. W. Yang and T. Fang, “On the accuracy of image normalization by Zernike moments,” Image Vis. Comput. 28, 403–413 (2010).

[CrossRef]

M. Pohit, “Neural network model for rotation invariant recognition of object shapes,” Appl. Opt. 49, 4144–4151 (2010).

[CrossRef]

G. A. Papakostas, Y. S. Boutalis, D. A. Karras, and B. G. Mertzios, “Pattern classification by using improved wavelet compressed Zernike moments,” Appl. Math. Comput. 212, 162–176 (2009).

[CrossRef]

J. Revaud, G. Lavoue, and A. Baskurt, “Improving Zernike moments comparison for optimal similarity and rotation angle retrieval,” IEEE Trans. Pattern Anal. Machine Intel. 31, 627–636 (2009).

[CrossRef]

A. P. Vivanco, G. U. Serrano, F. G. Agustin, and A. C. Rodriguez, “Comparative analysis of pattern reconstruction using orthogonal moments,” Opt. Eng. 46, 017002 (2007).

[CrossRef]

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

[CrossRef]

C. Y. Wee and R. Paramesran, “On the computational aspects of Zernike moments,” Image Vis. Comput. 25, 967–980(2007).

[CrossRef]

L. Kotoulas and I. Andreadis, “Accurate calculation of image moments,” IEEE Trans. Image Process. 16, 2028–2037(2007).

[CrossRef]

G. A. Papakostas, Y. S. Boutalis, C. N. Papaodysseus, and D. K. Fragoulis, “Numerical error analysis in Zernike moments computation,” Image Vis. Comput. 24, 960–969 (2006).

[CrossRef]

A. S. Mian, M. Bennamoun, and R. Owens, “3D model-based object recognition and segmentation in cluttered scenes,” IEEE Trans. Pattern Anal. Machine Intel. 28, 1584–1600 (2006).

[CrossRef]

C. W. Chong, R. Paramesran, and R. Mukundan, “A comparative analysis of algorithms for fast computation of Zernike moments,” Pattern Recogn. 36, 731–742 (2003).

[CrossRef]

R. G. Donald, I. Fung, and J. H. Shapiro, “Maximum-likelihood multiresolution laser radar range imaging,” IEEE Trans. Image Process. 6, 36–46 (1997).

[CrossRef]

A. Khotanzad and J. J. H. Liou, “Recognition and pose estimation of unoccluded three-dimensional objects from a two-dimensional perspective view by banks of neural networks,” IEEE Trans. Neural Netw. 7, 897–906 (1996).

[CrossRef]

J. T. J. Green and J. H. Shapiro, “Detecting objects in three-dimensional laser radar range images,” Opt. Eng. 33, 865–874 (1994).

J. T. J. Green and J. H. Shapiro, “Maximum-likelihood laser radar range profiling with the expectation-maximization algorithm,” Opt. Eng. 31, 2343–2354 (1992).

F. Stein and G. Medioni, “Structural indexing: efficient 3D object recognition,” IEEE Trans. Pattern Anal. Machine Intel. 14, 125–145 (1992).

[CrossRef]

A. Khotanzad and Y. H. Hong, “Invariant image recognition by Zernike moments,” IEEE Trans. Pattern Anal. Machine Intel. 12, 489–497 (1990).

[CrossRef]

L. K. Hansen and P. Salamon, “Neural network ensembles,” IEEE. Trans. Pattern Anal. Machine Intel. 12, 993–1001 (1990).

M. Teague, “Image analysis via the general theory of moments,” J. Opt Soc. Am. 70, 920–930 (1980).

[CrossRef]

M. K. Hu, “Visual pattern recognition by moment invariants,” IRE Trans. Inf. Theory 8, 179–187 (1962).

H. Abdi and L. J. Williams, “Principal component analysis,” WIREs Comp. Stat. 2, 433–459 (2010).

[CrossRef]

A. P. Vivanco, G. U. Serrano, F. G. Agustin, and A. C. Rodriguez, “Comparative analysis of pattern reconstruction using orthogonal moments,” Opt. Eng. 46, 017002 (2007).

[CrossRef]

L. Kotoulas and I. Andreadis, “Accurate calculation of image moments,” IEEE Trans. Image Process. 16, 2028–2037(2007).

[CrossRef]

A. Antonio, M. Pilar, and S. Santiago, “3D scene retrieval and recognition with depth gradient images,” Pattern Recogn. Lett. 32, 1337–1353 (2011).

[CrossRef]

J. Revaud, G. Lavoue, and A. Baskurt, “Improving Zernike moments comparison for optimal similarity and rotation angle retrieval,” IEEE Trans. Pattern Anal. Machine Intel. 31, 627–636 (2009).

[CrossRef]

A. S. Mian, M. Bennamoun, and R. Owens, “3D model-based object recognition and segmentation in cluttered scenes,” IEEE Trans. Pattern Anal. Machine Intel. 28, 1584–1600 (2006).

[CrossRef]

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

[CrossRef]

G. A. Papakostas, Y. S. Boutalis, D. A. Karras, and B. G. Mertzios, “Pattern classification by using improved wavelet compressed Zernike moments,” Appl. Math. Comput. 212, 162–176 (2009).

[CrossRef]

G. A. Papakostas, Y. S. Boutalis, C. N. Papaodysseus, and D. K. Fragoulis, “Numerical error analysis in Zernike moments computation,” Image Vis. Comput. 24, 960–969 (2006).

[CrossRef]

B. Steder, G. Greisetti, and G. W. Burgard, “Robust place recognition for 3D range data based on point features,” in Proceedings of the 2010 IEEE International Conference on Robotics and Automation (ICRA) (IEEE, 2010), pp. 1400–1405.

B. J. Chen, H. Z. Shu, H. Zhang, G. Chen, C. Toumoulin, J. L. Dillenseger, and L. M. Luo, “Quaternion Zernike moments and their invariants for color image analysis and object recognition,” Signal Process. 92, 308–318 (2012).

[CrossRef]

B. J. Chen, H. Z. Shu, H. Zhang, G. Chen, C. Toumoulin, J. L. Dillenseger, and L. M. Luo, “Quaternion Zernike moments and their invariants for color image analysis and object recognition,” Signal Process. 92, 308–318 (2012).

[CrossRef]

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

[CrossRef]

Z. Chen and S. K. Sun, “A Zernike moment phase-based descriptor for local image representation and matching,” IEEE Trans. Image Process. 19, 205–219 (2010).

[CrossRef]

C. W. Chong, R. Paramesran, and R. Mukundan, “A comparative analysis of algorithms for fast computation of Zernike moments,” Pattern Recogn. 36, 731–742 (2003).

[CrossRef]

B. J. Chen, H. Z. Shu, H. Zhang, G. Chen, C. Toumoulin, J. L. Dillenseger, and L. M. Luo, “Quaternion Zernike moments and their invariants for color image analysis and object recognition,” Signal Process. 92, 308–318 (2012).

[CrossRef]

R. G. Donald, I. Fung, and J. H. Shapiro, “Maximum-likelihood multiresolution laser radar range imaging,” IEEE Trans. Image Process. 6, 36–46 (1997).

[CrossRef]

Z. W. Yang and T. Fang, “On the accuracy of image normalization by Zernike moments,” Image Vis. Comput. 28, 403–413 (2010).

[CrossRef]

G. A. Papakostas, Y. S. Boutalis, C. N. Papaodysseus, and D. K. Fragoulis, “Numerical error analysis in Zernike moments computation,” Image Vis. Comput. 24, 960–969 (2006).

[CrossRef]

R. G. Donald, I. Fung, and J. H. Shapiro, “Maximum-likelihood multiresolution laser radar range imaging,” IEEE Trans. Image Process. 6, 36–46 (1997).

[CrossRef]

N. J. Mitra, L. Guibas, J. Giesen, and M. Pauly, “Probabilistic fingerprints for shapes,” in Proceedings of Symposium on Geometry Processing (ACM, 2006), pp. 121–130.

R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd ed. (Prentice Hall, 2002).

J. T. J. Green and J. H. Shapiro, “Detecting objects in three-dimensional laser radar range images,” Opt. Eng. 33, 865–874 (1994).

J. T. J. Green and J. H. Shapiro, “Maximum-likelihood laser radar range profiling with the expectation-maximization algorithm,” Opt. Eng. 31, 2343–2354 (1992).

B. Steder, G. Greisetti, and G. W. Burgard, “Robust place recognition for 3D range data based on point features,” in Proceedings of the 2010 IEEE International Conference on Robotics and Automation (ICRA) (IEEE, 2010), pp. 1400–1405.

N. J. Mitra, L. Guibas, J. Giesen, and M. Pauly, “Probabilistic fingerprints for shapes,” in Proceedings of Symposium on Geometry Processing (ACM, 2006), pp. 121–130.

L. K. Hansen and P. Salamon, “Neural network ensembles,” IEEE. Trans. Pattern Anal. Machine Intel. 12, 993–1001 (1990).

A. Khotanzad and Y. H. Hong, “Invariant image recognition by Zernike moments,” IEEE Trans. Pattern Anal. Machine Intel. 12, 489–497 (1990).

[CrossRef]

M. K. Hu, “Visual pattern recognition by moment invariants,” IRE Trans. Inf. Theory 8, 179–187 (1962).

A. E. Johnson, “A representation for 3-D surface matching,” Ph.D. dissertation (Robotics Institute, Carnegie Mellon University, 1997).

G. A. Papakostas, Y. S. Boutalis, D. A. Karras, and B. G. Mertzios, “Pattern classification by using improved wavelet compressed Zernike moments,” Appl. Math. Comput. 212, 162–176 (2009).

[CrossRef]

A. Khotanzad and J. J. H. Liou, “Recognition and pose estimation of unoccluded three-dimensional objects from a two-dimensional perspective view by banks of neural networks,” IEEE Trans. Neural Netw. 7, 897–906 (1996).

[CrossRef]

A. Khotanzad and Y. H. Hong, “Invariant image recognition by Zernike moments,” IEEE Trans. Pattern Anal. Machine Intel. 12, 489–497 (1990).

[CrossRef]

L. Kotoulas and I. Andreadis, “Accurate calculation of image moments,” IEEE Trans. Image Process. 16, 2028–2037(2007).

[CrossRef]

J. Revaud, G. Lavoue, and A. Baskurt, “Improving Zernike moments comparison for optimal similarity and rotation angle retrieval,” IEEE Trans. Pattern Anal. Machine Intel. 31, 627–636 (2009).

[CrossRef]

Z. J. Liu, Q. Li, Z. W. Xia, and Q. Wang, “Target recognition for small samples of ladar range image using classifier ensembles,” Opt. Eng. 51, 087201 (2012).

[CrossRef]

A. Khotanzad and J. J. H. Liou, “Recognition and pose estimation of unoccluded three-dimensional objects from a two-dimensional perspective view by banks of neural networks,” IEEE Trans. Neural Netw. 7, 897–906 (1996).

[CrossRef]

Z. J. Liu, Q. Li, Z. W. Xia, and Q. Wang, “Target recognition for small samples of ladar range image using classifier ensembles,” Opt. Eng. 51, 087201 (2012).

[CrossRef]

B. J. Chen, H. Z. Shu, H. Zhang, G. Chen, C. Toumoulin, J. L. Dillenseger, and L. M. Luo, “Quaternion Zernike moments and their invariants for color image analysis and object recognition,” Signal Process. 92, 308–318 (2012).

[CrossRef]

F. Stein and G. Medioni, “Structural indexing: efficient 3D object recognition,” IEEE Trans. Pattern Anal. Machine Intel. 14, 125–145 (1992).

[CrossRef]

G. A. Papakostas, Y. S. Boutalis, D. A. Karras, and B. G. Mertzios, “Pattern classification by using improved wavelet compressed Zernike moments,” Appl. Math. Comput. 212, 162–176 (2009).

[CrossRef]

A. S. Mian, M. Bennamoun, and R. Owens, “3D model-based object recognition and segmentation in cluttered scenes,” IEEE Trans. Pattern Anal. Machine Intel. 28, 1584–1600 (2006).

[CrossRef]

N. J. Mitra, L. Guibas, J. Giesen, and M. Pauly, “Probabilistic fingerprints for shapes,” in Proceedings of Symposium on Geometry Processing (ACM, 2006), pp. 121–130.

G. E. Smith and B. G. Mobasseri, “Robust through-the-wall radar image classification using a target-model alignment procedure,” IEEE Trans. Image Process. 21, 754–767 (2012).

[CrossRef]

C. W. Chong, R. Paramesran, and R. Mukundan, “A comparative analysis of algorithms for fast computation of Zernike moments,” Pattern Recogn. 36, 731–742 (2003).

[CrossRef]

A. S. Mian, M. Bennamoun, and R. Owens, “3D model-based object recognition and segmentation in cluttered scenes,” IEEE Trans. Pattern Anal. Machine Intel. 28, 1584–1600 (2006).

[CrossRef]

G. A. Papakostas, Y. S. Boutalis, D. A. Karras, and B. G. Mertzios, “Pattern classification by using improved wavelet compressed Zernike moments,” Appl. Math. Comput. 212, 162–176 (2009).

[CrossRef]

G. A. Papakostas, Y. S. Boutalis, C. N. Papaodysseus, and D. K. Fragoulis, “Numerical error analysis in Zernike moments computation,” Image Vis. Comput. 24, 960–969 (2006).

[CrossRef]

G. A. Papakostas, Y. S. Boutalis, C. N. Papaodysseus, and D. K. Fragoulis, “Numerical error analysis in Zernike moments computation,” Image Vis. Comput. 24, 960–969 (2006).

[CrossRef]

C. Y. Wee and R. Paramesran, “On the computational aspects of Zernike moments,” Image Vis. Comput. 25, 967–980(2007).

[CrossRef]

C. W. Chong, R. Paramesran, and R. Mukundan, “A comparative analysis of algorithms for fast computation of Zernike moments,” Pattern Recogn. 36, 731–742 (2003).

[CrossRef]

N. J. Mitra, L. Guibas, J. Giesen, and M. Pauly, “Probabilistic fingerprints for shapes,” in Proceedings of Symposium on Geometry Processing (ACM, 2006), pp. 121–130.

A. Antonio, M. Pilar, and S. Santiago, “3D scene retrieval and recognition with depth gradient images,” Pattern Recogn. Lett. 32, 1337–1353 (2011).

[CrossRef]

J. Revaud, G. Lavoue, and A. Baskurt, “Improving Zernike moments comparison for optimal similarity and rotation angle retrieval,” IEEE Trans. Pattern Anal. Machine Intel. 31, 627–636 (2009).

[CrossRef]

A. P. Vivanco, G. U. Serrano, F. G. Agustin, and A. C. Rodriguez, “Comparative analysis of pattern reconstruction using orthogonal moments,” Opt. Eng. 46, 017002 (2007).

[CrossRef]

L. K. Hansen and P. Salamon, “Neural network ensembles,” IEEE. Trans. Pattern Anal. Machine Intel. 12, 993–1001 (1990).

A. Antonio, M. Pilar, and S. Santiago, “3D scene retrieval and recognition with depth gradient images,” Pattern Recogn. Lett. 32, 1337–1353 (2011).

[CrossRef]

A. P. Vivanco, G. U. Serrano, F. G. Agustin, and A. C. Rodriguez, “Comparative analysis of pattern reconstruction using orthogonal moments,” Opt. Eng. 46, 017002 (2007).

[CrossRef]

R. G. Donald, I. Fung, and J. H. Shapiro, “Maximum-likelihood multiresolution laser radar range imaging,” IEEE Trans. Image Process. 6, 36–46 (1997).

[CrossRef]

J. T. J. Green and J. H. Shapiro, “Detecting objects in three-dimensional laser radar range images,” Opt. Eng. 33, 865–874 (1994).

J. T. J. Green and J. H. Shapiro, “Maximum-likelihood laser radar range profiling with the expectation-maximization algorithm,” Opt. Eng. 31, 2343–2354 (1992).

B. J. Chen, H. Z. Shu, H. Zhang, G. Chen, C. Toumoulin, J. L. Dillenseger, and L. M. Luo, “Quaternion Zernike moments and their invariants for color image analysis and object recognition,” Signal Process. 92, 308–318 (2012).

[CrossRef]

C. Singh and E. Walia, “Fast and numerically stable methods for the computation of Zernike moments,” Pattern Recogn. 43, 2497–2506 (2010).

[CrossRef]

G. E. Smith and B. G. Mobasseri, “Robust through-the-wall radar image classification using a target-model alignment procedure,” IEEE Trans. Image Process. 21, 754–767 (2012).

[CrossRef]

B. Steder, G. Greisetti, and G. W. Burgard, “Robust place recognition for 3D range data based on point features,” in Proceedings of the 2010 IEEE International Conference on Robotics and Automation (ICRA) (IEEE, 2010), pp. 1400–1405.

F. Stein and G. Medioni, “Structural indexing: efficient 3D object recognition,” IEEE Trans. Pattern Anal. Machine Intel. 14, 125–145 (1992).

[CrossRef]

Z. Chen and S. K. Sun, “A Zernike moment phase-based descriptor for local image representation and matching,” IEEE Trans. Image Process. 19, 205–219 (2010).

[CrossRef]

M. Teague, “Image analysis via the general theory of moments,” J. Opt Soc. Am. 70, 920–930 (1980).

[CrossRef]

B. J. Chen, H. Z. Shu, H. Zhang, G. Chen, C. Toumoulin, J. L. Dillenseger, and L. M. Luo, “Quaternion Zernike moments and their invariants for color image analysis and object recognition,” Signal Process. 92, 308–318 (2012).

[CrossRef]

A. P. Vivanco, G. U. Serrano, F. G. Agustin, and A. C. Rodriguez, “Comparative analysis of pattern reconstruction using orthogonal moments,” Opt. Eng. 46, 017002 (2007).

[CrossRef]

C. Singh and E. Walia, “Fast and numerically stable methods for the computation of Zernike moments,” Pattern Recogn. 43, 2497–2506 (2010).

[CrossRef]

Z. J. Liu, Q. Li, Z. W. Xia, and Q. Wang, “Target recognition for small samples of ladar range image using classifier ensembles,” Opt. Eng. 51, 087201 (2012).

[CrossRef]

Q. Wang, L. Wang, and J. F. Sun, “Rotation-invariant target recognition in LADAR range imagery using model matching approach,” Opt. Express 18, 15349–15360 (2010).

[CrossRef]

C. Y. Wee and R. Paramesran, “On the computational aspects of Zernike moments,” Image Vis. Comput. 25, 967–980(2007).

[CrossRef]

H. Abdi and L. J. Williams, “Principal component analysis,” WIREs Comp. Stat. 2, 433–459 (2010).

[CrossRef]

R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd ed. (Prentice Hall, 2002).

Z. J. Liu, Q. Li, Z. W. Xia, and Q. Wang, “Target recognition for small samples of ladar range image using classifier ensembles,” Opt. Eng. 51, 087201 (2012).

[CrossRef]

D. Xiao and L. Yang, “Gait recognition using Zernike moments and BP neural network,” in Proceedings of IEEE International Conference on Networking, Sensing and Control (IEEE, 2008), pp. 418–423.

D. Xiao and L. Yang, “Gait recognition using Zernike moments and BP neural network,” in Proceedings of IEEE International Conference on Networking, Sensing and Control (IEEE, 2008), pp. 418–423.

Z. W. Yang and T. Fang, “On the accuracy of image normalization by Zernike moments,” Image Vis. Comput. 28, 403–413 (2010).

[CrossRef]

B. J. Chen, H. Z. Shu, H. Zhang, G. Chen, C. Toumoulin, J. L. Dillenseger, and L. M. Luo, “Quaternion Zernike moments and their invariants for color image analysis and object recognition,” Signal Process. 92, 308–318 (2012).

[CrossRef]

G. A. Papakostas, Y. S. Boutalis, D. A. Karras, and B. G. Mertzios, “Pattern classification by using improved wavelet compressed Zernike moments,” Appl. Math. Comput. 212, 162–176 (2009).

[CrossRef]

S. Chang and C. P. Grover, “Pattern recognition with generalized centroids and subcentroids,” Appl. Opt. 44, 1372–1380 (2005).

[CrossRef]

A. Stern, I. Kruchakov, E. Yoavi, and N. S. Kopeika, “Recognition of motion-blurred images by use of the method of moments,” Appl. Opt. 41, 2164–2171 (2002).

[CrossRef]

M. Pohit, “Neural network model for rotation invariant recognition of object shapes,” Appl. Opt. 49, 4144–4151 (2010).

[CrossRef]

R. G. Donald, I. Fung, and J. H. Shapiro, “Maximum-likelihood multiresolution laser radar range imaging,” IEEE Trans. Image Process. 6, 36–46 (1997).

[CrossRef]

L. Kotoulas and I. Andreadis, “Accurate calculation of image moments,” IEEE Trans. Image Process. 16, 2028–2037(2007).

[CrossRef]

Z. Chen and S. K. Sun, “A Zernike moment phase-based descriptor for local image representation and matching,” IEEE Trans. Image Process. 19, 205–219 (2010).

[CrossRef]

G. E. Smith and B. G. Mobasseri, “Robust through-the-wall radar image classification using a target-model alignment procedure,” IEEE Trans. Image Process. 21, 754–767 (2012).

[CrossRef]

A. Khotanzad and J. J. H. Liou, “Recognition and pose estimation of unoccluded three-dimensional objects from a two-dimensional perspective view by banks of neural networks,” IEEE Trans. Neural Netw. 7, 897–906 (1996).

[CrossRef]

F. Stein and G. Medioni, “Structural indexing: efficient 3D object recognition,” IEEE Trans. Pattern Anal. Machine Intel. 14, 125–145 (1992).

[CrossRef]

A. S. Mian, M. Bennamoun, and R. Owens, “3D model-based object recognition and segmentation in cluttered scenes,” IEEE Trans. Pattern Anal. Machine Intel. 28, 1584–1600 (2006).

[CrossRef]

A. Khotanzad and Y. H. Hong, “Invariant image recognition by Zernike moments,” IEEE Trans. Pattern Anal. Machine Intel. 12, 489–497 (1990).

[CrossRef]

J. Revaud, G. Lavoue, and A. Baskurt, “Improving Zernike moments comparison for optimal similarity and rotation angle retrieval,” IEEE Trans. Pattern Anal. Machine Intel. 31, 627–636 (2009).

[CrossRef]

L. K. Hansen and P. Salamon, “Neural network ensembles,” IEEE. Trans. Pattern Anal. Machine Intel. 12, 993–1001 (1990).

Z. W. Yang and T. Fang, “On the accuracy of image normalization by Zernike moments,” Image Vis. Comput. 28, 403–413 (2010).

[CrossRef]

G. A. Papakostas, Y. S. Boutalis, C. N. Papaodysseus, and D. K. Fragoulis, “Numerical error analysis in Zernike moments computation,” Image Vis. Comput. 24, 960–969 (2006).

[CrossRef]

C. Y. Wee and R. Paramesran, “On the computational aspects of Zernike moments,” Image Vis. Comput. 25, 967–980(2007).

[CrossRef]

M. K. Hu, “Visual pattern recognition by moment invariants,” IRE Trans. Inf. Theory 8, 179–187 (1962).

M. Teague, “Image analysis via the general theory of moments,” J. Opt Soc. Am. 70, 920–930 (1980).

[CrossRef]

A. P. Vivanco, G. U. Serrano, F. G. Agustin, and A. C. Rodriguez, “Comparative analysis of pattern reconstruction using orthogonal moments,” Opt. Eng. 46, 017002 (2007).

[CrossRef]

J. T. J. Green and J. H. Shapiro, “Detecting objects in three-dimensional laser radar range images,” Opt. Eng. 33, 865–874 (1994).

J. T. J. Green and J. H. Shapiro, “Maximum-likelihood laser radar range profiling with the expectation-maximization algorithm,” Opt. Eng. 31, 2343–2354 (1992).

Z. J. Liu, Q. Li, Z. W. Xia, and Q. Wang, “Target recognition for small samples of ladar range image using classifier ensembles,” Opt. Eng. 51, 087201 (2012).

[CrossRef]

C. W. Chong, R. Paramesran, and R. Mukundan, “A comparative analysis of algorithms for fast computation of Zernike moments,” Pattern Recogn. 36, 731–742 (2003).

[CrossRef]

C. Singh and E. Walia, “Fast and numerically stable methods for the computation of Zernike moments,” Pattern Recogn. 43, 2497–2506 (2010).

[CrossRef]

A. Antonio, M. Pilar, and S. Santiago, “3D scene retrieval and recognition with depth gradient images,” Pattern Recogn. Lett. 32, 1337–1353 (2011).

[CrossRef]

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

[CrossRef]

B. J. Chen, H. Z. Shu, H. Zhang, G. Chen, C. Toumoulin, J. L. Dillenseger, and L. M. Luo, “Quaternion Zernike moments and their invariants for color image analysis and object recognition,” Signal Process. 92, 308–318 (2012).

[CrossRef]

H. Abdi and L. J. Williams, “Principal component analysis,” WIREs Comp. Stat. 2, 433–459 (2010).

[CrossRef]

D. Xiao and L. Yang, “Gait recognition using Zernike moments and BP neural network,” in Proceedings of IEEE International Conference on Networking, Sensing and Control (IEEE, 2008), pp. 418–423.

R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd ed. (Prentice Hall, 2002).

A. E. Johnson, “A representation for 3-D surface matching,” Ph.D. dissertation (Robotics Institute, Carnegie Mellon University, 1997).

N. J. Mitra, L. Guibas, J. Giesen, and M. Pauly, “Probabilistic fingerprints for shapes,” in Proceedings of Symposium on Geometry Processing (ACM, 2006), pp. 121–130.

B. Steder, G. Greisetti, and G. W. Burgard, “Robust place recognition for 3D range data based on point features,” in Proceedings of the 2010 IEEE International Conference on Robotics and Automation (ICRA) (IEEE, 2010), pp. 1400–1405.