ACTA AERONAUTICAET ASTRONAUTICA SINICA >
CIBA Moment Invariants and Their Use in Spacecraft Recognition Algorithm
Received date: 2013-07-12
Revised date: 2013-09-28
Online published: 2013-10-10
Supported by
National Natural Science Foundation of China (60974105,61104188); Aeronautical Science Foundation of China (20100152003)
In order to solve the non-robustness for affine moment invariants with changing illumination conditions and unknown blurring, an illumination and blur invariant is proposed which is based on the gray light model, image blurring theory and basic moment invariants theory. Combining the geometric affine moment invariants with the proposed illumination and blur invariants, the combined illumination, blur and affine (CIBA) moment invariants are built and their invariant features of illumination, blur and similarity transform (i.e. rotation, scaling and translation) are theoretically proved. Taking multiple images of three spacecraft models as examples, the average recognition accuracy by using CIBA moment invariants in a linear minor distance classifier can reach 86.37%, which is a 94.00% improvement compared with the affine moment invariants, and a 24.54% improvement as compared with the illumination moment invariants. CIBA moment invariants can effectively solve the problem in the identification of spacecraft under different conditions of illumination, unknown blurring and pose. They enhance the target recognition robustness which is based on moment invariants.
XU Guili , XU Jing , WANG Biao , TIAN Yupeng , GUO Ruipeng , LV Wen . CIBA Moment Invariants and Their Use in Spacecraft Recognition Algorithm[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2014 , 35(3) : 857 -867 . DOI: 10.7527/S1000-6893.2013.0403
[1] Wang X X, Yang Y S, Jing Z L. Space target recognition based on improved kernel FCM[J]. Chinese Space Science and Technology, 2012, 32(2): 35-42. (in Chinese) 王晓雪, 杨永胜, 敬忠良. 基于改进核聚类算法的空间目标识别方法[J]. 中国空间科学技术, 2012, 32(2): 35-42.
[2] Li L R, Shen C L, Wang C Q. Recognition method of aerial targets based on BP neural network[J]. Fire Control & Command Control, 2012, 37(12): 132-139. (in Chinese) 李丽荣, 沈春林, 王从庆. 基于BP神经网络的空中目标识别方法[J]. 火力与指挥控制, 2012, 37(12): 132-139.
[3] Flusser J, Suk T. Degraded image analysis: an invariant approach[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(6): 590-603.
[4] Suk T, Flusser J. Combined blur and affine moment invariants and their use in pattern recognition[J]. Pattern Recognition, 2003, 36(12): 2895-2907.
[5] Ji H J, Zhu H Q. Degraded image analysis using zernike moment invariants[C]//IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2009: 1941-1944.
[6] Liu J. Construction of feature invariants and its application in object recognition[D]. Wuhan: Huazhong University of Science and Technology, 2004. (in Chinese) 刘进. 不变量特征的构造及在目标识别中的应用[D]. 武汉: 华中科技大学, 2004.
[7] Dai X B, Zhang H, Shu H Z, et al. Image recognition by combined invariants of Legendre moment[C]//Proceedings of the 2010 IEEE International Conference on Information and Automation, 2010: 1793-1798.
[8] Paschalakis S, Lee P. Combined geometric transformation and illumination invariant object recognition in RGB color images[C]//Proceedings of 15th International Conference on Pattern Recognition, 2000: 584-587.
[9] Mindru F, Tuytelaars T, van Gool L, et al. Moment invariants for recognition under changing viewpoint and illumination[J]. Computer Vision and Image Understanding, 2004, 94(1-3): 3-27.
[10] Suk T, Flusser J. Affine moment invariants of color images[M]//Computer Analysis of Images and Patterns. New York: Springer, 2009: 334-341.
[11] Lu Y. Stability of moment invariants and their applications in 3-D object recognition[D]. Wuhan: Huazhong University of Science and Technology, 2007. (in Chinese) 路鹰. 不变矩稳定性及在三维目标识别中的应用[D].武汉: 华中科技大学, 2007.
[12] Liu J, Zhang T X. Fast algorithm for generation of moment invariants[J]. Pattern Recognition, 2004, 37(8): 1745-1756.
[13] Wang Y P, Huang X S, Li X L, et al. Moment invariants of gray distorted based on Hu Moments[J]. Journal of Dalian Maritime University, 2008, 34(4): 23-27. (in Chinese) 王亦平, 黄新生, 李晓雷, 等. 一种新的灰度变化不变矩[J]. 大连海事大学学报, 2008, 34(4): 23-27.
[14] Xu G L, Zhong Z W, Wang B, et al. Research on the construction of moment invariants of the geometry and illumination invariance[J]. Acta Aeronautica et Astronautica Sinica, 2013, 34(7): 1698-1705. (in Chinese) 徐贵力, 钟志伟, 王彪, 等. 具有几何和光照不变性的不变矩构建研究[J]. 航空学报, 2013, 34(7): 1698-1705.
[15] Gong M, Hu P, Cao W G, et al. A kind of shape-color moment invariants[C]//International Conference on Computer-Aided Design and Computer Graphics, 2011: 425-432.
[16] Hu M K. Visual pattern recognition by moment invariants[J]. IRE Transactions on Information Theorem, 1962, 8(2): 179-187.
[17] Suk T, Flusser J. Affine moment invariants generated by graph method[J]. Pattern Recognition, 2011, 44(9): 2047-2056.
[18] Gevers T, Smeulders A W M. Color-based object recognition[J]. Pattern Recognition, 1999, 32(3): 453-464.
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