PT Unknown
AU Adria Molina
   Lluis Gomez
   Oriol Ramos Terrades
   Josep Llados
TI A Generic Image Retrieval Method for Date Estimation of Historical Document Collections
BT Document Analysis Systems.15th IAPR International Workshop, (DAS2022)
PY 2022
BP 583–597
VL 13237
DI 10.1007/978-3-031-06555-2_39
DE Date estimation; Document retrieval; Image retrieval; Ranking loss; Smooth-nDCG
AB Date estimation of historical document images is a challenging problem, with several contributions in the literature that lack of the ability to generalize from one dataset to others. This paper presents a robust date estimation system based in a retrieval approach that generalizes well in front of heterogeneous collections. We use a ranking loss function named smooth-nDCG to train a Convolutional Neural Network that learns an ordination of documents for each problem. One of the main usages of the presented approach is as a tool for historical contextual retrieval. It means that scholars could perform comparative analysis of historical images from big datasets in terms of the period where they were produced. We provide experimental evaluation on different types of documents from real datasets of manuscript and newspaper images.
ER