Publication: Visual Script and Language Identification

Authors: Anguelos Nicolaou, Andrew D. Bagdanov, Lluis Gomez i Bigorda, and Dimosthenis Karatzas

Published in: DAS 2016

In this paper we introduce a script identification method based on hand-crafted texture features and an artificial neural network. The proposed pipeline achieves near state-of-the-art performance for script identification of video-text and state-of-the-art performance on visual language identification of handwritten text. More than using the deep network as a classifier, the use of its intermediary activations as a learned metric demonstrates remarkable results and allows the use of discriminative models on unknown classes. Comparative experiments in video-text and text in the wild datasets provide insights on the internals of the proposed deep network.


bibtex: | @article{nicolaou2016visual, title={Visual Script and Language Identification}, author={Nicolaou, Anguelos and Bagdanov, Andrew D and Gomez i Bigorda, Lluis and Karatzas, Dimosthenis}, journal={arXiv preprint }, year={2016} } —

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