Publication: Visual Script and Language Identification


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


Published in: DAS 2016


Abstract:
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.


pdf

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} } —

Aditional Resources:

NA

Experimental data and reproducabillity:

NA



Creative Commons License
Any work in this page other than source code or program binaries is licensed under a Creative Commons Attribution 4.0 International License. When applicable atribution should be in the form of a citation.