【摘要】 以前许多文章曾介绍过一些基于手写体的书写人身份识别技术 ,其中多数都假设所写的文本是固定的。本文中 ,我们试图通过一种自动的不依赖文本的书写人识别的新颖算法 ,来消除这种假设。假定不同人的手写体存在明显的区别 ,我们采用一种综合方法 ,它基于纹理分析 ,每个人的手写体都被看成一种不同的纹理。原则上 ,我们可以采用任意一种标准的纹理识别算法 (例如 :多通道伽柏滤波器方法 )。在对 40名书写人的 1 0 0 0份测试文档的分类中 ,测试结果非常令人满意 ,识别率最高达到了 96 %。更多还原

【Abstract】 Many techniques have been reported for handwriting-based writer identification. The majority of techniques assume that the written text is fixed.In this paper we attempt to eliminate this assumption by presenting a novel algorithm for automatic text-independent writer identification.Given that the handwriting of different people is often visually distinctive,we take a global approach based on texture analysis,where each writer’s handwriting is regarded as a different texture.In principle, this allows us to apply any standard texture recognition algorithm for the task (e.g.,the multi-channel Gabor filtering technique).Results of 96% accuracy on the classification of 1000test documents from 40 writers are very promising.更多还原