Sebastian Sudholt, Leonard Rothacker and Gernot A. Fink
Proc. Int. Conf. on Document Analysis and Recognition, 2017.
Kyoto, Japan
A word spotting system is in large parts characterized by the query modalities it is able to process. The most common modalities here are Query-by-Example and Query-by- String. However, recently a new query type has been proposed: In Query-by-Online-Trajectory (QbO) the query is presented as a set of online-handwritten trajectories. In this work we devise a cross-domain word spotting framework using CNNs which is able to accomplish the QbO task. In particular, we design two different QbO systems which we evaluate in a number of experiments. We are not only able to outperform the current state of the art in QbO word spotting but also show that a system using a single CNN for both online and offline data achieves superior results compared to a system that uses a CNN for each domain individually.