An Invariance Algorithm of Synergetic Pattern Recognition
SHAO Jing1,2, GAO Jun1,2, XU XiaoHong1
1.Department of Computer and Information, Hefei University of Technology, Hefei 230009 2.Center for Biomimetic Sensing and Control Research, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031
Abstract:A synergetic invariance algorithm is proposed in this paper. Through the influential dynamic theory of synergetic pattern recognition, the parameters of the affine transform are gotten. The right pattern can be gotten by the dynamic evolvement of the order parameters and the autoadaptive or the nationalization of the prototype to testing patterns. This method avoids the processing of frequency field utilized by the Fourier transform. And it is similar to the recognition of human being. The validity and robustness of the algorithm are demonstrated by the experiments.
[1] Gao J, Dong H M, Chen D G, Gan L, Dong W W. Research on Synergetic Fingerprint Classification and Matching. In: Proc of the 2nd IEEE International Conference on Machine Learning and Cybernetics. Xi’an, China, 2003, Ⅴ: 3066-3071 [2] Dong H M, Gao J, Hu L M, Wang A D. Synergetic Fingerprint Recognition Based on PCA Neural Network. Pattern Recognition and Artificial Intelligence, 2004, 17(1): 87-93 (in Chinese) (董火明, 高 隽, 胡良梅, 王安东. 基于PCA网络的协同指纹识别. 模式识别与人工智能, 2004, 17(1): 87-93) [3] Gao J, Dong H M, Shao J, Zhao J. Parameters Optimization of Synergetic Recognition Approach. Chinese Journal of Electronics, 2005, 14(2): 192-197 [4] Huang W Y, Cui J S, Lu X, Fan L. Translation Invariance of Synergetic Algorithm for Pattern Recognition. China Journal of Image and Graphics, 1996, 1(5-6): 391-395 (in Chinese) (黄婉云, 崔建生, 卢 洵, 范 玲. 模式识别协同算法的平移不变性. 中国图象图形学报, 1996, 1(5-6): 391-395) [5] Fan L, Lu Z H. Rotation and Scaling Invariance in Synergetic Algorithm for Pattern Recognition. Journal of Beijing Normal University(Natural Science), 1997, 33(1): 87-90 (in Chinese) (范 玲, 卢志恒. 模式识别协同算法的旋转缩放不变性. 北京师范大学学报(自然科学版), 1997, 33(1): 87-90) [6] Zhao T, Qi F H. Research on Spatial Invariant of Synergetic Neural Network. Journal of Shanghai Jiaotong University, 1998, 32(10): 34-38 (in Chinese) (赵 同, 戚飞虎. 协同神经网络的不变性研究. 上海交通大学学报, 1998, 32(10): 34-38) [7] Zhang J, Qi F H. Synergetic-Based PSRI Pattern Recognition Method. Journal of Shanghai Jiaotong University, 1998, 32(6): 1-3 (in Chinese) (张 军, 戚飞虎. 基于协同理论的不变性模式识别. 上海交通大学学报, 1998, 32(6): 1-3) [8] Haken H. Synergetic Computers and Cognition-A Top-Down Approach to Neural Nets. Berlin, Germary: Springer-Verlag, 1991 [9] Gao J. The Theory of Artificial Neural Networks and Simulation. Beijing, China: China Machine Press, 2003 (in Chinese) (高 隽. 人工神经网络原理及仿真实例. 北京: 机械工业出版社, 2003) [10] Yin H J, Qi F H, Ye X Y. A Learning Algorithm of Synergetic Neural Network Based on Pseudo-Inverse. Acta Electronica Sinica, 1999, 27(5):15-17 (in Chinese) (尹虎君, 戚飞虎, 叶芗芸. 基于伪逆的协同神经网络学习算法. 电子学报, 1999, 27(5):15-17)