基于自动分割的手写签名神经元平面建模
A Neuronal Planar Modeling for Handwriting Signature based on Automatic Segmentation
摘要：
针对脱机手写签名的鉴别问题，提出了一种签名图像的平面神经元模型。平面模型一般是基于划定均匀区的图像，我们提出了在本文中的自动分割方法到频带的签名图像。签名图像由一个平面神经元模型和一个水平的二级模型和一个垂直的主模型组成。所提出的方法已在两个数据库上进行了测试。第一个是我们收集的;它包括6000个签名，对应60个作家。第二个是公共的GPDS-300数据库，包括16200个签名，对应于300人。实验结果令人鼓舞。
英文摘要：
This paper deals with offline handwriting signature verification.We propose a planar neuronal model of signature image. Planarmodelsare generally based on delimiting homogenous zones ofimages; we propose in this paper an automatic segmentationapproach into bands of signature images. Signature image ismodeled by a planar neuronal model with horizontal secondarymodels and a verticalprincipal model. The proposed methodhas been tested on two databases. The first is the one we havecollected; it includes 6000 signaturescorresponding to 60writers. The second is the public GPDS-300 database including16200 signature corresponding to 300 persons. The achievedresults are promising.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
