On the automatic text detection and recognition algorithms for maritime images

Cornelia Nita; Marijke Vandewal

doi:10.1117/12.2599422

12 September 2021 On the automatic text detection and recognition algorithms for maritime images

Cornelia Nita, Marijke Vandewal

Proceedings Volume 11870, Artificial Intelligence and Machine Learning in Defense Applications III; 118700B (2021) https://doi.org/10.1117/12.2599422
Event: SPIE Security + Defence, 2021, Online Only

Abstract

In view of the increase in illicit maritime activities like piracy, sea robbery, trafficking of narcotics, immigration and illegal fishing, an enhance of accuracy in surveillance is essential in order to ensure safer, cleaner and more secure maritime and inland waterways. Recently, the field of deep learning technology has received a considerable attention for integration into the security systems and devices. Convolutional Neural Networks (CNN) are commonly used in application of object detection, segmentation and classification. In addition, they are used for text detection and recognition, mainly applied to automatic license plate recognition for the highway monitoring, rarely to the maritime situational awareness. In the current study, we propose to analyse the practical feasibility of applying an automatic text detection and recognition algorithm on ship images. We consider a two-stage procedure that localizes the text region and then decodes the prediction into a machine-readable format. In the first stage the text region in the scene is localized with computer-vision based algorithms and EAST model, whereas in the second stage the predicted region is decoded by the Tesseract Optical Character Recognition (OCR) engine. Our results demonstrate that the integration of such a feature into a vessel information system will most likely improve the overall situational awareness.

Conference Presentation

Citation Download Citation

Cornelia Nita and Marijke Vandewal "On the automatic text detection and recognition algorithms for maritime images", Proc. SPIE 11870, Artificial Intelligence and Machine Learning in Defense Applications III, 118700B (12 September 2021); https://doi.org/10.1117/12.2599422

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