Fast matching algorithm for scene matching aided navigation based on invariant moments

被引：1
|
作者：
Fu Y.-J. [1 ,2 ]
Cheng Y.-M. [1 ]
Pan Q. [1 ]
Sun K.-F. [3 ]
机构：
[1] College of Automation, Northwestern Polytechnical University
[2] The Telecommunication Engineering Institute, Air Force Engineering University
[3] Xi'an Precision Machinery Institute
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2011年 / 33卷 / 04期
关键词：
Camberra distance; Invariant moment; Matching time; Wavelet transform;
D O I：
10.3969/j.issn.1001-506X.2011.04.27
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
To improve the speed of scene matching based on invariant moments, a wavelet transform is used to compress searching space before matching, and then, to reduce the computational complexity of similarity measure at each point to be matched, the moments computation of each sub-image is simplified by using ten sum-tables in terms of the calculation characteristic of moments during matching. By integrating these two speed-up methods, a fast moment based scene matching algorithm is proposed, which decreases the computational cost greatly. Simulation results show that the proposed method takes less time with good precision compared with the pure wavelet transform matching.
引用
收藏
页码：847 / 850+861
相关论文
共 16 条
  • [1] Hu M.K., Visual pattern recognition by moment invariants, IRE Trans. on Information Theory, 8, 1, pp. 179-187, (1962)
  • [2] Chen K., Efficient parallel algorithms for the computation of two-dimensional image moments, Pattern Recognition, 23, 1-2, pp. 109-119, (1990)
  • [3] Yang L.R., Albregtsen F., Fast and exact computation of Cartesian geometric moments using discrete Green's theorem, Pattern Recognition, 29, 7, pp. 1061-1073, (1996)
  • [4] Belkamed K.S., Fast computation of 2-D image moments using biaxial transform, Pattern Recognition, 34, 9, pp. 1867-1887, (2001)
  • [5] Sossa A.H., Yanez M.C., Diaz J.L., Et al., Computing geometric moments using morphological erosions, Pattern Recognition, 34, 2, pp. 271-276, (2001)
  • [6] Chong Y.W., Raveendran P., Mukundan R., Fast computation of geometric moments using a symmetric kernel, Pattern Recognition, 41, pp. 2369-2380, (2008)
  • [7] Tong Z., Li T., Image matching with moment invariants based on genetic algorithms, Computer Engineering & Science, 24, 3, pp. 14-17, (2002)
  • [8] Zhang W., Tao Q.C., Luo D.S., Et al., Fast pedestrian detection based on wavelet templates compound with moment invariants matching, Journal of Zhengzhou Institute of Surveying and Mapping, 24, 1, pp. 40-42, (2007)
  • [9] Jane Y., A wavelet-based coarse-to-fine image matching scheme in a parallel virtual machine environment, IEEE Trans. on Image Processing, 9, 9, pp. 1547-1559, (2000)
  • [10] Hong G., Zhang Y., Wavelet-based image registration technique for high-resolution remote sensing images, Computers & Geosciences, 34, pp. 1708-1720, (2008)
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