JSEA  Vol.6 No.5 , May 2013
Robust Performance of Scene Matching Algorithm
ABSTRACT
Performance analysis is very important in the study and design of scene matching algorithm. Based on the analysis of the common performance parameters, robustness of scene matching algorithm is defined, including the definitions of robust stability and robust performance, and the corresponding evaluation parameters matching margin and matching adaptability are given. With application of these robustness parameters on 8 scene matching algorithms, quantitative analysis results of algorithm robustness are obtained. The paper provides an important theoretical reference to the performance evaluation of scene matching algorithm.

Cite this paper
Z. Xia, X. Yang, F. Meng and S. Wang, "Robust Performance of Scene Matching Algorithm," Journal of Software Engineering and Applications, Vol. 6 No. 5, 2013, pp. 6-10. doi: 10.4236/jsea.2013.65B002.
References
[1]   R. Missaoui, M. Sarifuddin, et al., “Similarity Measures for Efficient Content-based Image Retrieval,” IEEE Proceedings on Vision, Image and Signal Process, 2005, pp. 875- 887.

[2]   G. Abdul, N. I. Rao, Shoab and K., “Robust Image Matching Algorithm,” 4th EURASIP Conference focused on Vider/ Image Processing and Multimedia Communications, 2003, pp. 155-160.

[3]   J. Li and J. Ma, “An Improved Edge Detection Algorithm,” Computer Development & Applications, Vol. 24, No. 1, 2011, pp. 71-73.

[4]   J. B. Wang, X. M. Lu and Z. He, “An Improved Algorithm of Image Registration Based on Fast Robust Features,” Computer Engineering & Science, Vol. 33, No. 2, 2011, pp. 112-117.

[5]   Z. Xiong, F. Chen, D. Wang and J. Y. Liu, “Robust Scene Matching Algorithm for SAR/INS Integrated Navigation System Based on SURF,” Journal of Nanjing University of Aeronautics & Astronautics, Vol. 43, No. 1, 2011, pp. 49-54.

[6]   Z. G. Ling, Y. Liang, Q. Pan, H. Shen and Y. M. Cheng, “A Robust Multi-level Scene Matching Algorithm for Infrared and Visible Light Image,” Acta Aeronautica Et Astronautica Sinica, Vol. 31, No. 6, 2010, pp. 1185-1195.

[7]   Y. Li and W. H. Zhang, “Study of Scene Matching Algorithm Based on Edge Strength,” Tactical Missile Technology, Vol. 2, 2010, pp. 59-63.

[8]   B. Han and Y. M. Wang, “Research of Image Matching Based on a Fast Normalized Cross Correlation Algorithm,” Acta Armamentarii, Vol. 31, No. 2, 2010, pp. 160-165.

[9]   Y. G. Yang, S. Zuo and X. X. Huang, “Integral Experiment and Simulation System for Image Matching,” Journal of System Simulation, Vol. 22, No. 6, 2010, pp. 1270-1273.

[10]   S. M. Zhang, Y. Chen and Y. Lin, “Robust Algorithm of Matching SAR Image to Optical Image Using Multiple Subarea,” Journal of Tongji University, Vol. 37, No. 1, 2009, pp. 121-125.

[11]   F. Meng, X. G. Yang and P. Sun, “A Novel Filtering and Fusion Algorithm for Sequence Image Matching Navigation,” 2008 International Congress on Image and Signal Processing, Vol. 4, 2008, pp. 668-671.

[12]   X. B. Wang, G. S. Xu and S. W. Liu, “Research on the Simulation of Forward-looking Image in the Infrared Imaging Guidance,” Infrared and Laser Engineering, Vol. 35, No. 10, 2006, pp. 68-72.

[13]   F. W. Zhao, J. C. Li and Z. K. Shen, “Study of Scene Matching Techniques,” Systems Engineering and Electronics, Vol. 24, No. 12, 2002, pp.111-114.

[14]   K. M. Zhou, J. C. Doyle and K. Glover, Robust and Optimal Control. Prentice Hall, Englewood Cliffs, New Jersey, 1996.

[15]   Y. J. Zhang, “Image Engineering (2): Image Analysis,” Tsinghua University Press, 2005.

 
 
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