2018-12-19 Welcome guest,  Sign In  |  Sign Up
Chin. Opt. Lett.
 Home  List of Issues    Issue 01 , Vol. 03 , 2005    Morphological self-organizing feature map neural network with applications to automatic target recognition


Morphological self-organizing feature map neural network with applications to automatic target recognition
Shijun Zhang, Zhongliang Jing, Jianxun Li
Institute of Aerospace Information and Control, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200030

Chin. Opt. Lett., 2005, 03(01): pp.12-12-

DOI:
Topic:Image processing
Keywords(OCIS Code): 100.0100  100.5010  200.4260  

Abstract
The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real-world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.

Copyright: © 2003-2012 . This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 View PDF (255 KB)

Share:


Received:2004/5/8
Accepted:
Posted online:

Get Citation: Shijun Zhang, Zhongliang Jing, Jianxun Li, "Morphological self-organizing feature map neural network with applications to automatic target recognition," Chin. Opt. Lett. 03(01), 12-12-(2005)

Note: This work was supported by the National Natural Science Foundation of China (No. 60304007, 60375008), China PH.D Discipline Special Foundation (No. 20020248029), China Aviation Science Foundation (No. 02D57003), Aerospace Supporting Technology Foundation (No. 2003-1.3 02), and Key Project of Shanghai Science and Technology Development Foundation (No. 015115038). S. Zhang's e-mail address is zhangshijun@sjtu.edu.cn.



References

1. Y. Won, P. D. Gader, and P. C. Coffield, IEEE Trans. Networks 8, 1195 (1997).

2. M. A. Khabou, P. D. Gader, J. M. Keller, in CVBVS'99 Proceedings 1999, 101 (1999).

3. N. Yu, H. Wu, C. Y. Wu, F. M. Li, and L. D. Wu, Science in China (series F) 46, 262 (2003).

4. http://www.ph.tn.tudelft.nl/Courses/FIP/noframes/fip-Segmenta.html.

5. T. Kohonen, in Proceedings of the IEEE 78, 1464 (1990).

6. W. T. Freeman and E. H. Adelson, IEEE Trans. Pattern Analysis and Machine Intelligence 13, 891 (1991).

7. Y. He, T. J. Feng, J. K. Cao, X. Q. Ding, and Y. H. Zhou, in IEEE Conf. MLC 3, 1279 (2002).

8. R. P. Lippmann, IEEE ASSP Mag. 4, 4 (1987).


Save this article's abstract as
Copyright©2018 Chinese Optics Letters 沪ICP备15018463号-7 公安备案沪公网安备 31011402005522号