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一种目标识别中基于关键点的仿射不变矩

吴高洁 李 超 熊 璋

吴高洁, 李 超, 熊 璋等 . 一种目标识别中基于关键点的仿射不变矩[J]. 北京航空航天大学学报, 2009, 35(9): 1043-1047.
引用本文: 吴高洁, 李 超, 熊 璋等 . 一种目标识别中基于关键点的仿射不变矩[J]. 北京航空航天大学学报, 2009, 35(9): 1043-1047.
Wu Gaojie, Li Chao, Xiong Zhanget al. Affine invariant based on determinant points in object recognition[J]. Journal of Beijing University of Aeronautics and Astronautics, 2009, 35(9): 1043-1047. (in Chinese)
Citation: Wu Gaojie, Li Chao, Xiong Zhanget al. Affine invariant based on determinant points in object recognition[J]. Journal of Beijing University of Aeronautics and Astronautics, 2009, 35(9): 1043-1047. (in Chinese)

一种目标识别中基于关键点的仿射不变矩

详细信息
    作者简介:

    吴高洁(1983-),男,湖北荆州人,硕士生,wugaojie1983@163.com.

  • 中图分类号: TP 391.4

Affine invariant based on determinant points in object recognition

  • 摘要: 针对常用仿射不变矩对轮廓边缘信息敏感的特点,提出了一种基于关键点的局部仿射不变矩,以分割出来的物体灰度图像为基础,首先计算出物体的质心,然后以质心为扩展点向周围引伸出多条射线,寻找每条射线方向上的最近灰度极值点,将所有灰度极值点当作关键点集合,并按照文中提出的计算仿射不变矩的方法提取出多阶不变矩,将其当作神经网络的输入向量,放入已经训练好的神经网络来达到识别物体的目的,将此方法应用在了飞机图像的识别上,实验结果证明此方法在物体轮廓分割不完整和有噪点污染的情况下能保持很好的稳健性,简单有效并具有较广的应用范围.

     

  • [1] Hu M K. Visual pattern recognition by moment invariants[J]. IRE transforms Theory, 1962: 179-187 [2] Khotanzad A, Hong Y H. Invariant image recognition by Zernike moments[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(5):489-497 [3] Esa R, Mikko S, Janne H. Affine invariant pattern recognition using multiscale auto-convolution[J].IEEE Transaction on Pattern Analysis and Machine Intelligence, 2005, 27(6): 908-918 [4] Resis T H. The revised fundamental theorem of moment invariants[J]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 1991, 13(8): 830-834 [5] Kadyrov K, Petrou M. The trace transform and its application[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(8):811-828 [6] Tomas S, Jan F. Combined blur and affine moments invariant and their use in pattern recognition[J]. Pattern Recognition, 2003, 36: 2895-2907 [7] David L. Distinctive image features from scale-invariant key points[J]. International Journal of Computer Vision, 2004, 60(2): 99-110 [8] ObdrZalek S, Matas J. Object recognition using local affine frames on distinguished regions[J].Proceedings of the British Machine Vision Conference,2002:113-122 [9] Lazebnik S, Schmid C, Ponce J. A sparse texture representation using local affine regions[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(8):1265-1278 [10] Lazebnik S,Schmid C,Ponce J. Sparse texture representation using affine-invariant neighborhoods[J]. Proceeding of IEEE Conference on Computer Vision and Pattern Recognition (CVPR03), 2003:319-342 [11] Zhang H Y, Yang X Q, Guo HT. Aircraft image recognition based on affine transformation[J]. Acta Aeronautics and Astronautics, 2003:15-20 [12] Cai H P, Lei L, Su Y. An affine invariant region detector using the 4th differential invariant Proceedings of 19th IEEE International Conference on Tools with Artificial Intelligence. Washington,DC:IEEE Computer Siciety,2007,1:540-543
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出版历程
  • 收稿日期:  2008-08-04
  • 网络出版日期:  2009-09-30

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