中文摘要：

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。

英文摘要：

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.