笔迹识别作为一种身份识别技术,具有自然,非入侵等优点,因此成为模式识别和机器学习领域的一个研究热点。本文提出了一种与文本无关的笔迹识别方法,该方法利用独立分量分析(Independent Component Analysis , ICA)来提取笔迹的纹理特征,并利用竞争学习方法确定笔迹的特征编码。实验结果证明利用该方法进行笔迹识别具有很好的效果。
Abstract
Writer recognition , as an identification technology , has many advantages , such as natural interaction and non-intrusive detection , thus it becomes a hot topic in pattern recognition and machine learning research area. This paper proposes a new writer recognition algorithm of text independent , which adopts Independent Component Analysis (ICA) to extract texture feature and competitive learning mechanism to determine the center of class. Experimental results show that our algorithm is efficient .
关键词
人工智能 /
模式识别 /
笔迹识别 /
独立分量分析 /
竞争学习
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Key words
artificial intelligence /
pattern recognition /
writer recognition /
independent component analysis /
competitive learning
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参考文献
[1] M. Ozaki , Y. Adachi , N. Ishii , Writer Recognition by means of Fuzzy Similarity Evaluation Function [C] , 4th International Conference on Knowledge-Based Intelligent Engineering Systems & Allied Technologies , 2000 , 287 - 291.
[2] 朱勇,谭铁牛,王蕴红. 基于笔迹的身份鉴别[J] . 自动化学报,2001. 27 (2) : 229 - 233.
[3] D. A. Valkaniotics , J. Sirigos , et al , Text-Independent Off-line Writer Recognition Using Neural Networks [C] , ICECS , 1996 , 692 - 695.
[4] B. A. Olshausen , D. I. Field , Sparse Coding With an Overcomplete Basis Set : A Strategy employed by V1 ? [J] , Vision Research , 1997 , 37 :3311 - 3325.
[5] A. Hyv?rinen , P. O. Hoyer , Emergence of Topography and Complex Cell Properties from Natural Images using Extensions of ICA [C] , Advances in Neural Information Processing Systems , 2000 , 12 : 827 - 833.
[6] A. Hyv?rinen , E. Oja , Independent Component Analysis : Algorithms and Application [J] , Neural Networks , 2000 , 13 (4 - 5) : 411 - 430.
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脚注
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基金
教育部博士点基金资助项目(20020004005)
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PDF(372 KB)
