A modification of a stopping method for text recognition in a video stream with best frame selection

Ilya Tolstov; Stanislav Martynov; Vera Farsobina; Konstantin Bulatov

doi:10.1117/12.2586928

4 January 2021 A modification of a stopping method for text recognition in a video stream with best frame selection

Ilya Tolstov, Stanislav Martynov, Vera Farsobina, Konstantin Bulatov

Proceedings Volume 11605, Thirteenth International Conference on Machine Vision; 116051M (2021) https://doi.org/10.1117/12.2586928
Event: Thirteenth International Conference on Machine Vision, 2020, Rome, Italy

Abstract

One of the most important problem in constructing computer vision systems for embedded and mobile devices is offline recognition of text strings. In this paper, we analyze the problem of text strings recognition process in a video stream using best frame selection. This method allows to incorporate the information from multiple views of the same target object, thus increasing the overall extraction accuracy. A stopping method is proposed, which allows to make an automatic stopping decision, i.e. to terminate the process at the optimal time in order to maximize the responsiveness of the system. Experimental evaluation on open identity document datasets MIDV-500 and MIDV-2019 show that the proposed stopping rule allows to decrease mean error level of the text recognition results in comparison with a baseline approach which stops after a fixed amount of processed frames.

Citation Download Citation

Ilya Tolstov, Stanislav Martynov, Vera Farsobina, and Konstantin Bulatov "A modification of a stopping method for text recognition in a video stream with best frame selection", Proc. SPIE 11605, Thirteenth International Conference on Machine Vision, 116051M (4 January 2021); https://doi.org/10.1117/12.2586928

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