A statistical model for writer verification
A statistical model for writer verification
复制标题
作者验证的统计模型
DOI：
10.1109/icdar.2005.33
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发表时间：
2005
期刊：
影响因子：
--
通讯作者：
Vivek Shah
中科院分区：
文献类型：
--
作者：
S. Srihari;Matthew J. Beal;Karthik Bandi;Vivek Shah
一个统计模型，用于确定是否一对文件，一个已知的和一个有问题的，是由同一个人写的建议。该模型有以下四个组成部分：（i）区分要素，例如，从每个文档中提取全局特征和字符;（ii）计算来自每个文档的对应元素之间的差异;（iii）使用每个差异的条件概率估计，针对文档由相同或不同作者撰写的假设计算对数似然比（LLR）;条件概率估计本身是使用高斯或伽马估计从标记样本中确定的，假设它们的统计独立性;以及（iv）分析相同和不同作者LLR的LLR分布，以将证据的强度校准到被询问的文件检查者使用的标准九点量表中。该模型示出了一组特定的鉴别元素的实验结果。
A statistical model for determining whether a pair of documents, a known and a questioned, were written by the same individual is proposed. The model has the following four components: (i) discriminating elements, e.g., global features and characters, are extracted from each document; (ii) differences between corresponding elements from each document are computed; (iii) using conditional probability estimates of each difference, the log-likelihood ratio (LLR) is computed for the hypotheses that the documents were written by the same or different writers; the conditional probability estimates themselves are determined from labeled samples using either Gaussian or gamma estimates for the differences assuming their statistical independence; and (iv) distributions of the LLRs for same and different writer LLRs are analyzed to calibrate the strength of evidence into a standard nine-point scale used by questioned document examiners. The model is illustrated with experimental results for a specific set of discriminating elements.