基于关键词提取的手写汉字文本依存笔迹鉴别技术

Writer verification for Chinese handwritten document based on keywords extraction

针对文本独立笔迹鉴别技术中需要大篇幅文档以提取图像纹理等笔迹信息的限制条件,和传统文本依存笔迹鉴别技术中需要内容完全相同的笔迹文档的限制条件,本文提出了一种新的文本依存笔迹鉴别技术.它以局部特征匹配与投票为手段进行关键词提取,对提取出的相同关键词建立训练集,在两篇文档的相同关键词之间进行匹配,将笔迹鉴别问题转化为签名识别问题.实验结果表明,在文档内容不完全相同的情况下,该技术仍然能够有效地对文档进行笔迹鉴别.

In text independent handwriting verification, lengthy documents are required to extract image textures and other handwriting features; while in text dependent handwriting verification, the contents of the comparing documents are required to be identical. In order to overcome these confinements, this paper presents a novel text dependent handwriting verification technique. In the process, keywords are extracted based on matching and voting of local features, then same keywords are used to build training sets, and these train sets of two documents are compared, so the handwriting verification problem is transformed into signature identification. The experiment results show this method can work effectively under the condition that the contents of two documents are not identical.