文献图像检索的多域智能系统

D. Barbuzzi, A. Massaro, A. Galiano, L. Pellicani, G. Pirlo, Matteo Saggese
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引用次数: 3

摘要

本文提出了一种基于多领域智能系统的文档图像检索实验分析。更具体地说,在同一文件图像上,讨论了三个不同领域的组合:布局,标志和签名。该方法对多域系统提供的每一个决策进行分析,从而在训练阶段使用与之前训练样本置信度不同的新样本来更新系统。分别使用DTW、欧氏距离和余弦相似度对版面、logo和签名进行分析。最后,考虑了个体决策的加权组合。在13个不同公司的30个旋转表单上进行的实验结果表明,基于ANR性能指标,所提出的方法相对于单域检索系统具有优越性。ANR参数能够对多域系统进行评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-domain intelligent system for document image retrieval
This paper presents an experimental analysis on document image retrieval using a multi-domain intelligent system. More specifically, on the same document image, the combination of three different domains: layout, logo and signature are discussed. This new method analyses every single decision provided by multi-domain system so that, in the training phase, a new sample classified with a dissimilar confidence to the previous trained samples is used to update the system. DTW, Euclidean distance and cosine similarity have been used, respectively for the analysis of layout, logo and signature. Finally, the weighted combination of individual decisions was considered. The experimental results, carried out on 30 rotated forms belonging to 13 different companies, demonstrate the superiority of the proposed approach with respect to single-domain retrieval systems, based on the ANR performance index. The ANR parameter is able to evaluate the multi-domain system.
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