Отрывок: Weighted combination of per-frame recognition results for text recognition… Petrova O., Bulatov K., Arlazarov V.V., Arlazarov V.L. Компьютерная оптика, 2021, том 45, №1 DOI: 10.18287/2412-6179-CO-795 83 Previous work [55] described experiments performed on the MIDV-500 [16] dataset. This dataset contains 500 video clips of identity documents captured with mobile cameras without strong distortion. However, it seems im- portant to evaluate the quality of the proposed method a...
Название : Weighted combination of per-frame recognition results for text recognition in a video stream
Авторы/Редакторы : Petrova, O.
Bulatov, K.
Arlazarov, V.V.
Arlazarov, V.L.
Ключевые слова : mobile OCR
video stream
anytime algorithms
weighted combination
ensemble methods
Дата публикации : Фев-2021
Издательство : Самарский национальный исследовательский университет
Библиографическое описание : Petrova O, Bulatov K, Arlazarov VV, Arlazarov VL. Weighted combination of per-frame recognition results for text recognition in a video stream. Computer Optics 2021, 45(1): 77-89. DOI: 10.18287/2412-6179-CO-795.
Серия/номер : 45;1
Аннотация : The scope of uses of automated document recognition has extended and as a result, recognition techniques that do not require specialized equipment have become more relevant. Among such techniques, document recognition using mobile devices is of interest. However, it is not always possible to ensure controlled capturing conditions and, consequentially, high quality of input images. Unlike specialized scanners, mobile cameras allow using a video stream as an input, thus obtaining several images of the recognized object, captured with various characteristics. In this case, a problem of combining the information from multiple input frames arises. In this paper, we propose a weighing model for the process of combining the per-frame recognition results, two approaches to the weighted combination of the text recognition results, and two weighing criteria. The effectiveness of the proposed approaches is tested using datasets of identity documents captured with a mobile device camera in different conditions, including perspective distortion of the document image and low lighting conditions. The experimental results show that the weighting combination can improve the text recognition result quality in the video stream, and the per-character weighting method with input image focus estimation as a base criterion allows one to achieve the best results on the datasets analyzed.
URI (Унифицированный идентификатор ресурса) : https://dx.doi.org/10.18287/2412-6179-CO-795
http://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Weighted-combination-of-perframe-recognition-results-for-text-recognition-in-a-video-stream-87755
Другие идентификаторы : Dspace\SGAU\20210228\87755
Располагается в коллекциях: Журнал "Компьютерная оптика"

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