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褶皱中文手写体身份鉴别 被引量：2

Wrinkled Chinese Handwriting-Based Writer Identification
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摘要 针对褶皱中文笔迹身份鉴别的问题,提出了一种基于散射变换系数统计特性的识别方法,主要利用散射变换的局部平移不变性和弹性形变稳定性等特性,先将文本图像进行散射变换,再采用伽玛模型,对其各子带的散射系数提取分布特征作为全局特征,然后在全局特征上建立Copula模型,最后使用Copula模型之间的KL距离计算相似性,用于身份鉴别。理论分析和对比实验结果表明,对于不同褶皱的文本图像,基于散射变换统计特性的识别方法优于现有的方法。 Targeting at the problem of wrinkled Chinese handwriting recognition, this paper presents a method based on statistical characteristics of scattering transform coefficients. This method mainly uses the local translational invariance and the stability of elastic deformation of scattering transform. Firstly, the text image is transformed by scattering. The distribution characteristics used as global characteristics are extracted by applying gamma model to scattering coefficients of sub-bands. Then the copula model is constructed based on these global characteristics. Finally, the similarities are calculated for recognizing writers by using the Kullback-Leibler divergence between copula models. Theoretical analysis and comparative experiment show that our method based on statistical characteristics of scattering transform is more advantageous than the others for when regarding text images with various degrees of wrinkles.
作者 尚赵伟 曹海 陈波
机构地区 重庆大学计算机学院
出处 《电子科技大学学报》 EI CAS CSCD 北大核心 2015年第1期72-78,共7页 Journal of University of Electronic Science and Technology of China
基金 国家自然科学基金(61173130) 重庆市自然科学基金(CSTC-2010BB2217)
关键词 COPULA模型 伽玛分布 KL距离 散射变换 Copula model gamma distribution kullback-leibler divergence scattering transform
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献16

  • 1李昕,丁晓青,彭良瑞.一种基于微结构特征的多文种文本无关笔迹鉴别方法[J].自动化学报,2009,35(9):1199-1208. 被引量：30
  • 2DUVERNOY J. Handwriting synthesis and classification by means of space-variant transform and density and Karhunen -Loeve analysis[J]. J Opt Soc Am, 1975,65: 1331-1336.
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  • 4SAID SHE, TAN T N, BAKER K D. Personal identification base on handwriting[J]. Pattern Recognition and Artificial Intelligence, 2000, 33(1): 149-160.
  • 5HE Z Y, TANG Y Y. Chinese handwriting-based writer identification based on contourlet[C]IIIEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2005). Hawaii, USA: IEEE, 2005: 1058-1063.
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  • 8XU Da-yuan, SHANG Zhao-wei. Hand writing-based writer identification with complex wavelet[C]lIInternational Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). HongKong, China: IEEE, 2008: 597-601.
  • 9朱贝贝,尚赵伟,袁博,国庆,张峰,杨建伟.抗混叠轮廓波变换的脱线中文手写体笔迹识别[J].计算机工程与应用,2011,47(24):150-153. 被引量：6
  • 10朱贝贝.脱线中文手写体笔迹识别[D].重庆大学,2011:28-36.

二级参考文献16

  • 1Plamondon R, Lorette G. Automatic signature verification and writer identification -- the state of the art. Pattern Recognition, 1989, 22(2): 107-131.
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共引文献33

同被引文献16

引证文献2

二级引证文献4

电子科技大学学报
2015年 第1期

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