Airplane extraction and identification by improved PCNN with wavelet transform and modified Zernike moments

Imaging Science Journal

Volumn 62, Issue 1, 2014, Pages 27-34

  Wang, W X ^a   Zhou, W G ^b   Zhao, X M ^a  

^a CHANG'AN UNIVERSITY   (China)

^b UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

Airplane identification; PCNN; Wavelet transform; Zernike moments

Indexed keywords

IDENTIFICATION ALGORITHMS; IMAGE SEGMENTATION ALGORITHM; PCNN; PROCESSING SPEED; PULSE COUPLED NEURAL NETWORK; SATELLITE REMOTE SENSING; SEGMENTED OBJECTS; ZERNIKE MOMENTS;

AIRCRAFT; AIRPORT SECURITY; AIRPORTS; ALGORITHMS; EXTRACTION; IMAGE RECONSTRUCTION; NEURAL NETWORKS; WAVELET TRANSFORMS;

IMAGE SEGMENTATION;

EID: 84893157306     PISSN: 13682199     EISSN: 1743131X     Source Type: Journal    
DOI: 10.1179/1743131X12Y.0000000033     Document Type: Article

References (21)

1. Gérard, Y. A fast and elementary algorithm for digital plane recognition. Electron. Notes Discrete Math., 2003, 12, 142-153.
2. Wang, L., Chao, X. and Yan, J. Aircraft recognition based on nonparametrical statistics, Proc. 7th Int. Conf. on Natural computation: ICNC 2011, Shanghai, China, July 2011, IEEE, pp. 1602-1606.
3. Das, S. and Bhanu, B. A system for model-based object recognition in perspective aerial image. Pattern Recogn., 1998, 31, 465.
4. Zhang, M. C., Wu X. Q. and Wang P. W. Aircraft recognition via extraction of closed contour and partial feature matching. Comput. Simul., 2006, 23, 193.
5. Eckhorn, R., Reitboeck, H. J., Arndt, M. and Dicke, P. Feature liking via synchronization among distributed assemblies: simulations of results from cat visual cortex. Neural Comput., 1990, 2, 293.
6. Johnson J. L. and Padgett M. L. PCNN models and applications. IEEE Trans. Neural Networks, 1999, 10, 480.
7. Li, M., Cai W. and Tan Z. Pulse coupled neural network based image fusion. Lect. Notes Comput. Sci., 2005, 3497, 741.
8. Muresan, R. C. Pattern recognition using pulse-coupled neural networks and discrete fourier transforms. Neurocomputing, 2003, 51, 487.
9. Haken, H. Pattern recognition and synchronization in pulsecoupled neural networks. Nonlinear Dyn., 2006, 44, 269.
10. Zhan, K., Zhang, H. J. and Ma, Y. D. New spiking cortical model for invariant texture retrieval and image processing. IEEE Trans. Neural Networks, 2009, 20, 1980-1986.
11. Wang, Z. B., Ma, Y. D., Cheng, F. Y. and Yang, L. Z. Review of pulse-coupled neural networks. Image Vis. Comput., 2010, 28, 5-13.
12. Skourikhine, A. N. Pulse couple neural network for image smoothing and segmentation, Proc. Int. Symp. on Computational intelligence: ISCI 2000, Kosice, Slovakia, August 2000, Slovak Neural Networks Group, Vol. 8, p. 9.
13. Kuntimad, G. and Ranganath, H. S. Perfect image segmentation using pulse coupled neural networks. IEEE Trans. Neural Networks, 1999, 10, 591.
14. Zhang, Y. D. and Wu, L. Image segmentation based on 2D Tsallis entropy with improved pulse coupled neural networks. J. Southeast Univ. (Nat. Sci. Ed.), 2008, 38, 579.
15. Peng, M., Jiang, B. and Xiao, J. A novel method of image segmentation based on parallelized firing PCNN. Acta Autom. Sin., 2008, 34, 1169.
16. Liu, M. F. and Hu, H. J. Evolutionary computation based optimization of image Zernike moments shape feature vector. Wuhan University J. Nat. Sci., 2008, 13, 153.
17. Yan, W. and Han, G. Q. Geometrically robust image watermarking using modified Zernike moments. Comput. Sci., 2009, 36, 247.
18. Nugroho, S. and Utomo, D. Rotation invariant indexing for image using Zernike moments and R-tree. Telkomnika, 2011, 9, 335-340.
19. Gao, X. B., Wang, Q., Li, X. L., Tao, D. C. and Zhang, K. B. Zernike-moment-based image super resolution. IEEE Trans. Image Process., 2011, 20, 2738-2747.
20. Ma, Z. M., Zhang, G. and Li, Y. Shape feature descriptor using modified Zernike moments. Pattern Anal. Appl., 2011, 14, 9-22.
21. Wang, W. X. Colony image acquisition system and segmentation algorithms. Opt. Eng., 2011, 50, 123001.